{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 语义分割和数据集\n",
    "\n",
    "最重要的语义分割数据集之一是[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "将所有输入的图像和标签读入内存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"读取所有VOC图像并标注。\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'SegmentationClass' ,f'{fname}.png'), mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "绘制前5个输入图像及其标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IsEyQOt07lRwRjxAxZyCkRCVgx4eUVZAKZw1KxSi4MTbl5LrkvYe1EQcEypsPyOuG3Tu3uPL2qyitYmDmBVLGA0OpjICPa8RHglEIAZ0XbF19kdXzl3jpnc/xH/2Xf/tU8+q9p9SC8z3PvcmEZt7SSkFPw7DocdhYpNBkWiEwBDujMQsW0wOMkownNaocYkSOLDOqLEfkqwSZ462hV+bIok+wDVpKculRYR+pG9BztIrOiURRzxWLhUAqRd4LFMLFfJkXqCDBS3zwCCeRjaSnc3KvMK1BG0/rPHlesbF1jn5vhS+883Oc2bpCVVToIkcgqCrD2TNn2ds/SNBwhD2aumG+mDA+fErVG8Y1lxyy0w4hQIoMKQJCw9OHT/ju7/xOQl1OQPSJLBN92HguBCHjWg1ieRaEE8+Jz0/IglQxFus4SkLGLJeMaMzl56/w+isvE/Ds7uzy//71X6etW5wziVgWHVAfN3KKStPvE7Hm2Hgdw5tCiiXkGEgGTMTrQSRjLANIwZnr13jj9beiA8jJbPuPH58ZtH8JRggRGrOuY2dFSFFKYp5ESLTS2GAJKYEa02Q+wjE+8ouEPCZUeAdCBiQyLQaJCuAkCG/ItGY46HNYDZjPJjjpkFJFj0mk2E5EyMz6EGFOEaFGRIpIRHroEnKL151lGWWvz2C0wmC0Tn+4wqC/QllVZDqLhIm0Ln0IhLQZXGJieZcILd7jvEXr/NRz6+Yztu7dB2+YzFs+d3GNyYMDtoSlePQxD977CLt3G7HYZ4BDXbqKOvcacv0K49bjb3yA1zrdDJZEFUSM0pQUOB+wISwjqo6ZF+gg0zhRgYCSKn5e5xPEE3Og3kWvuxs6wbrWxYi1o86IXo/J5bMMbj/kxt/+rynFAc/98p+lWt2M90dqQnA4Z5BKJNZbDkictYiONStgtLXJ6traqeZVCMFsXnNhOGR/0lAoQ5CakXK0doF0LqVSawb9IXvGRLhVC2SpyHRB3hug5Ai8o1dkmKAYCU8jJHWApp5Qiin9bAJyghYznHfMpwa3CMwOa7y1qBKGqxm9YUGGxPnASrlGmRU45zELw3y6oJIZQWiECxjjmS4a1ta2GA7O8sL1F3nu2suMhutYH5BSI2R8LSkEmc74/Dtv8/6NDwjB0zRthD59jHQe3r/H6to5lM6x1vxUaV+EQGlBUAEpM5QKEBwEj8eDTw6hjysysogSFiM8+AhbS58MVfCJQZ3IRzjiBdpPZNJ8ym0hBBJJs2iXuXjnWhazKU3dgnPJmEU2qgsh2siOpNZhDGGZIY9pEUJywuMVSBFi2kRAEAG5vA6VUEWPDJGw4gMYYl7vGMP4o+OZDFp/dS2snb+4pOUu6cjLn7sfu2lKDBqOiQCC4wcu77k4Tkme+PMnhvjR78WP/9tpxqflGMOPfn/8v+W3HTQXgO37dzna23vmy/Hes1jMl9GKkAJCNGJxzUiUznDexXla0qMjUyvISGgOwcUcmw8g08JPBsfLmFMT/vggLsse585dpG0bTLuDdB4vJFK66PF5idIS50TyGiVSxY0jCATRUZ4jdCiVQmtNWVUU/SFlNSAvSrKUP1NKobJId5ZSRkrxkryS8ojBH89t+vmnidDW+30GL77K3tMdVta3yGcHfO7wG0zvvId0U0QlKIo+4twXaAaXuLW/YOfDbe7c+Q6j86vUT3ZQvRwlRJp7wHmCip6kc37p2Xrn44EtFEIJRDhB1iAghcI6F/MWOpF6RED4SCfpoMvopUZoWSiFExGmjOx2gas028OSs4sxB3/wN9j5/u9x6Rf/PFe/9Kvk/QGgUFLjg0vesU2vLfE+Xkee98iyMq61U4wYzUty71gpYBFajDcEJ+jlEq81VsT7PF1YnKnp9XqQVRSFpmwlDoWWFlTGqDU8N5/x0vSQYXDc761wc1hy1zxle3+fo8MpQjl07vEtrG+VrJyTlGUFSmJqy2yywLSKagjWOObtgsl0zCgrkTjmdYsxLcY4nMt54dpLvPLK61x77lWqqo/OiuhwEZ0H5z2+aVBaopTmc+98nv/2b/531K3BOse8NrTWMl80lGWPo/0deqN1hFRkeXbqNSsEMU8tFVK1ROZWSExEkWBrEF2JR4IdQ/CI5I+qIBJBKCyNzKcaHLEsmIgRVAeJe0+iMy3tpgwd9f5E1Lek+HfnYnylsPx/90CSa92dGst3XJ5rIjl+AoEMnRG0mOBpiIzJn2DPns2grZ2/wP/2P//rZEqhtEKng0kpmQ7J7l+FkmL5u/j7CIdImQ7GFFrKbvPKjgHXHZ5dWBohs5Pfd5PfOcN/xNjBH7Vy4RP/fOLnmIuKXsDyRqXJ6/wB3+XbfUiHS4oiQsyZuBD49/7ELz7LdJ64aMF81mCtxVpHkWUEQGuFdZZAhlIZQrQx7yIEXqTwO4QUrbm0IiMzSqAQwaVcT5wl18EJUkZ4UkJZFVy4eBVBYPfpk0RMiJGDdIJMKpxNBJMT9ylOUkgs85j/0VlGXpaUZY+i6pGX1dKYLckgHNPWSVj/Mv4Q0ZAvb0NI5N2fghVy1NZ8495tzv723+Lly2v46TZ6tstaIVErVwjrz3HgS37v2z/gm9/8hwzLAaVQzPce88bodeaqwObxPjgEwnuc81hjYFmX0xmb+LMPAR0xFKRWaCXAe6wPKKHwREjYueSYEKIPkubHW58eEw1mIEYJznusdQTj8MIzaVvyPKc022z/5n/G02/9Dpe++he4+NbPocoCGWLEF50ih0AuS8FidC8+Ucv0LMN7j7Exqr64onjsNa51hLyPtFMqVTKxC6wzCJlT6kDwDWVW0DQ1XkgqrciCIJ+MufzgAUf7T/m6NJzNC3peMOz1EUXOZDLDh4b+qmR1vYfOMsaHMw5vLQguMm+rgWZjs896b8BaNsAYy3gyZjqdM/FzFgtDrjJ65Yi3Xn2d56+/xIWLV5E6p6gG5LqI0C0CgccaG6HF4JA+IJTizJktLl28wM3b96ibloPxhEGvpCpz8kwyn0/pr26Rl+Wp12tcEAIlY9ClFGgJAk8QcZ10p/qy3jEZLtGV8AgZc+HxYYnEEZZOYvf79MclekDntAEIlyBEn4yNJXiL9za+9vI8TGmCDjFKJms5llGaj4ZOiE8aVRGWez7ioB3AEaO6kP7eBCjorv9fUIQmACXTVzJGMUkZPX6potHSKbEo02OlDPH7kwYsfbZYG9IlMVn+TRJOfH9s1bvrWBoz8Udt18nHdR9/iRMfz/Py3w6XlSe9WalQSx8iMZdEwKfr8aEr9kyeR/jj0N1PH0opptMJtrW01lIWJfhYG9YaRwgyOg8dq4jjg/D43+hJBVKUI0KcXB/nPiCS9xaWnyquYUFZ5py/eBWtc/aePqapFzjnsMEhpej2QppHsSxijSQ/F8kfWay/ycseRdmnzHvkeYnO8lQgLk8YsuMb1105yzkVnV1OUduPucHPMAaF5MubNeeaj7CPMg4Wlrq8wODS63z71g7/5G/8N9y6+TE7B4e0TaRsb62tU2aKO0dHNNZxZXOLc0UfJ2y69/G1vWnRibATqfoeJSVFlqEzzTI6S7RqJePaCakQ2MqACw6NWBa8O+fRStFaH50ZG2vQYl5Bx8MtVxip+fa9Qz6ctPwbnzvDmb7EHX7Mw//2P2T7D/8eV375L3Pm1S8gswwpM6TQn0jGS6k+FZn45xnOeebzOZurI1YrxcxpDg8PaZsprZlQ6pbMgOpvMW0btFJ4B5kW5NLhybD1Edgp9354m8PxlDp4Ns5kuGEP2eQ0vYJqNGRFOLaPFuxu10wODYORZrCiuLjeZzSo6OUVtrGoIOnbnN0nhxzUEySC27cP6Fd9zm5u8cu/8Es8//xL5FmBLkp6g1GsB4RUChUZpwoBSmHaNp5rQuKsQQjJC88/z83bd1Ayo20a6nrBYjZnOOgTXI0Snkzrn0gt/+OGICB1KocRErprjF5sdHZIMF8qc1lu0BPRVFefGl+TlHoIySB6lhtweY7E74PoIsFUEQLJ6MkTj+KYmLZk1nZ5M7d8vdAZOCE5jhbjX4WIz+vO1y4yC0SyyzGOJ5dEqu6/TxvPZtBEZ6BAyZC+ogGLBit6kkqE9LuAlD4lzUl/+6QxW34v4mGm0r+RQxYN2TLG6M62H4nMfjRK48Tvu/FHjJnobkoXIUdvxScWmoxhzvFCSI+JjPMQsWrSYwmoT1QWPdvQWrG3f0hd11hjY9idID4hDCDTXMplsrm7ZLpSkBPQn5AS4aOHLxJNPH4+tYQlfUiEBqIjkec5Z89eJMsUu9uPmc3GeKdQMlHpESmylggZIxIpFUJEmLHIS/IyJysKsqIkz3O0ziPMqFRiVHWqDnKZV/rRGybDyXvVARSnH71c8fy5jDtHNXceBiZiFV8Iig/+Ib/1z97l0f6EHoZzm2ep2watZCS8SMl0voiep3NkWUaVaZAK7+M9yaSm6JXoVCAqUjTZIQyiU2MIJIp+gmp9ZI8iEyxkj4urQ4KOcDE34ayN9yqAlBrvPXWzoBEBJwO//9FTvnb7gL/0hYt89aVVhjmY7R9w5/9zg8fX3+HiL/9Vtp5/A6FUjO4RkXADCHF84D3r8N6zPx2zaTYI0jPMHHvOMT7aRWAYLw4gK/BWYYSmV1UUBZRZwIia4HYI6ojZOHBv/wAdAmdfeoutL/4Mv/CFzzEarWIFfHjzQ6a//3s83Nllda3H+WsleRUYFhWr5ZBcZATnCVgQmqNpzf7RnHnj2Fwf8ZXPP8frr77J1tZ5Nje3loeyzo6jKJUcDKVkzDs5jxKQa4UPDmNbrHUID++8+Ta/9Tu/S/CBpnUsmpjj1SqLxKZ2ii96mPb0LEeS0xiIQYKSqRhNBIJ3SBHLXJAdq9nTGahPQIBLrz2kKL2L6iLSFBHu8MnDsXMxhVxGdtFx98cQ54kXF8soqoM3/XJfHxv1Y9Qr2bCYO+681pRiWQYGgpTO6JxgC0mLKDi3ZEb+uPHMyQklIiVZddFZMkZayPT7ZNSWkdlxRCZFjNy6anSVojUhTkRjy4gsRQMnDt0OdvxRA/ZpBq2b8AiKHUvcLKMN0jLoPG4h8FInDDo6RBAhvQgrpRvmHc7YZZiens1PCoV/0shzzXQyoV7UiUHklpGUkslwCVLOKX4aCMscVHR+IvQgpVwaK3xUE3HORVjUmxh5WQhe4FNhNiHeB6Ulq+tn4obaEUyOJkjlkocoI5QhuohaLXM8WZaj82jMirKgyHOkViliT0QSme6dOPYGI15+4l51zgXQ4elieadON6x1/LV/+oQPD1quecX1n3uHr339azx++IAszzl77hxFaDE2btxIAggMS83+fMy8aZk0w2i0swyRZTircDYedDQSsjweQCLEw8cn+EbE2jqBSOSetBYT1Ngl1gUxSe5DNOhSKLyw2NZhjAXh0VolaryEOrBvar57dETRHzKtF/w/f/cW//C9Hn/5Zy7wledHjDC0d77Gx//Z97j/4s9y7Vf+CutXXojetwQ7P2B861u0RzunmtcQAtPJnL29fc5ubDDol2RaMJkvCMEidB+djdBFRa+vkH6fEPZonUXmsFKW5Nkat48aFrri2gtv8G/9r/7XvP7y8zze3eGf3bjB0ycP2X38gPW1VX7257+Aktvkuae2Da6xbM/2GOYVmpz5fB7LF7xGUfHitZd45603WFndYGV1Ha0y6rYlLwp6/T5K6eiMSkmeZQghcaaJedB0YBrT0tQ1Ukm01rjgOXvuPBtrK+zvj3HOMp3O2N8/IMszzm6uYOsjbLmCsfaPmcFPH4LEjhUOiTyWnApdrqmT5Amp9DApd6Q1FhmG7nhD+RO7LEGF3fuQqs6OI4UOdowKINFeigToHEdXxy93jPSExOCNm9hzErPqJOHiW6RoTXQGUZwgl4n097hOOwkzkQhnojuHP2U8M+QY4cT0hV8aJSlYGjclOshQnDBk6Xd03mv8vRQnH9dVhodPRGZLo5Y+UGeYTkZo3b/xyDj5+/iTtQats08+IiQIiGPPRSY8GFhK4nShukjGoWm6SEoew8LJAzrNyLRGSUvTNjE/40zcZIDSKtGEYw2U90sXJ33G6LnFSEDEzZjqupwPBKHJ8h65kOQp/+d8wKf8h3UGay3OWqy1GOOoeiusrp1jMZ8zn9dMJ3N0Fh0WHxzWt8f1TjKgZIbWUGSGQmcUuSfP/bI4tMuX/egIiQTRGTffAQ9pGiUh1qX8FEMJGBU5Z15+AfP4CQeHY/AOXRSIAO1iQhPAuADW47AUZREZltbTtC37R1OMtegsIws+5p1UIJBhjUErjdAZCrGUHwvOIXw8jKL7EfNm8bCUy8Mh0UlwLm7UDtJsrUsFwHFPOA9KC1TaGfOmxQRBpSSbwx5ra30K3/L/+M2P+K3Lq/xPvnyRNy9U9FzL+MPf4Qc3vsHgrV/m8pd+Gff0hxx8+Id854N77Oyfrg4NoGkbZouaxrb0vGZjdYXbO6sgQec5MtcovQvuKUUvKqgUOqOUBQqNbWDnqWW0dYkz117hg5sf8/33v8d4fESmFGfXVymvXsPXe4R2D+UL5nVNqAPtPDCe1fieo8oLZnWLliVvvfY5Lp2/ynBtHakUmcwxxhCQ9Ht98rI8ji1kLCFpmgUQRQWMsZH45KPGZ9sayrQePFCUJc9ff46Do3cJPtAaR20sh+Mjnu7tc+nCOYStyYveT7FqRXLmI/wiVcrNpr2+xOP50S9S7uyYwNTpYYoOljoxOqhvmRL/hPMYloFfJBdxTHI6acS6nFiXo+tgxZOHcjgmkkVkKRbJSiIGHwlmLNMN3bm8RDy66wSqskeWfTrr+RkjtIDAJ+gwfRHlQqP4Z7zIDnJRISYqlYiMlRitRSp54s4sc2MyJIgxTX40fMmQJOPWxVudX39CI2Fp5Lo5/KTvT2T3LcmjHZkh/utD9z7xeR2TxofufbobFpDBkSuJFhnWOVprYiguTprSZxtKazY3R7TNHO8dxjiKE3m0aDwiO7A1prsVxx+WkDRXO08nLs3WOoYr66ysbkXCQSfDtPSETqy6NAc+dEXNYakB6WwsdDXWYIzFGkPb1rStoTV1zCUsJiwmj4ApWgoyGSWQkL2kHZfukDhJ/vlk/HX8c+fbdff99EMAQ2Hoj4bsbz/hzre/HyFWqXE+alsG5zHO4pzHE9hcGWJMiyAWUwuVSiVSLtC7yOiUIdKI27bFE/Nn3h8bJbAopXDeL/dEEB5JZDi64AgpOjbOolAxTxvAtiZBKx4vZYTFkCADHo8LIHVMpkuVYaTjT790kbcuz/jt97f5P//GR3z1xQ3+wlsrXBoqyvqAyXf/Lt/4+m8xGEm+dueIv/GDp8xqc+q5bZqWo+mUwVFJryy4uLXBrZ1DxqZG5jOKfEpVWkqdo1QGAeq2wckaEaBZKMZjw+bmeZ7uPMKHQy5fvMJXfubLrK8O2Xn6iJvvfwM5vQPeIPOKjAqUYLiq6eU9nu4dIXuCt177Ei8+/wqj0SrOJcfNOoKyrKysoPMswm4I8jyjK4nwNkZkIaE4IXhaY9EyFtD3+1EoV0oRZcuU5tVXXuVb330XHwLGeY5mC9ZWhvSqAdPpHGd3WDl//adatFJGR1orgRIZ8aRMUU8QUcuVyHKmi36WjrpPpMLAJwzf8ng6GeWk53cbcbkhZTobfTSSnogm+K4izC+N2CfGEldMLxSW1nRpZOUyMddBMpFRfZKfFNWPTrDnhUf+kTf7o+OZIUcRbLresLTMsXapq1MKqBDpnScJHZJYO9UZKhFA4NJfEvQYxFK7axmFBZY4b9QwPI7EllFyuhPLg7G7yd3zgieYNlrM7klwwrPwOOuSSkM8yH2C74RKTLEQItPNuiV7UziPCDF53xjzE7HdnzSkFKysD6kXC5w1eBdVsQNEmrYxQLlk0R3f1tB9jHiwLQ1FglNDqsYnyoeK4NPcixj5JLFjmXJtJwsepVAJHkiv2e2y5Z6J0ar3jun4iO9+52vUixFHBzP6wVOUMsp4yZg/kylhetJ4nYQcl/cz3WdIDNOlq3e6IQSUYcbOD3/Ag/t36ZcVCI0PMSK13mONSzBvhPT6Zc5R24AAJQW9siQQaGyLD1FzUAQRFRGsizC7FHgRI2ORYi+HR1iLENGzrxcNsbuBQQhF8AGb3jcEsMFGsojzNHW9JMkUWY4PbQKHPK2JOb34d4mQklbA/VnDl6+e4bXXXuGf3JnzW9/5gH9842P+3Our/NnXVtkYOAbOMa4zXhkV/Py5ghsfndIJEwLnHOPJlEGvx8qiJuztcnZD4ZodyiKQC4mkwHlH29ZIIenJjJyS1hqcz3B2xvbOAza3zvNLP/enee2VNxgOKp48uc8Pvv6bVH5GkZc4lbE/OSJYFwW3g8U1iuefe4kvvPN5Lly+TrNoaJqaIi8RePKiSsLR0YFQSkYnIBG4orpG/NnZFp30FzMVCT29fh+dHJJA4g5ozetvvs3g7/wG0+kC7zzzec1s3vA0qYec2dIEf3pHoUMsukhHKht38AmmYrRHEbkJIbJvIUY/SypbImBEwXJg+byw3BtLY9a9c3fAJop/LIVN50gg5b1SqiJ10jj5xSfSCOIYVkwcg3iuHXd7OMbeUjF2F5EFT6LcLQOeE9b2U8ezGbQQwNkEcXXVGtHKWuMJShOUjAxBJXEpjFdao7VaJskkkSAgA+kQTQZPnLDKyZpDF0CnOgzRfaQ0WeEYCow312NsLEBWWIy1iBCoG0ufCryj9SIVAzpsiHJDnugsqMR0gohjSx9D/uADwRhcU+OIMOHh0TjVSWUcHY6Po6dnHQG2zp5hb3uSaNosc0gREnWAWuajjltbiOMwP41ofGRyfCRdse7e3i47T3fp9yrKoiQrcrJMk+mcbMlEjJ9ZCRXFRyV0gqsR0oyJ57jXQvIkI+nEGYdUGc5JjHURRtUaVJS66u7pyf/oHJnu2rvlHVL+MshEFjrdtHZjMZ+x/2jMoKgIQrFYLGjbFutsIt7IWIqiFL0ip9SaQ2+jIyUDuVZYE4kxIot0Ymcsbd3QOhvVQ6iiA7HMiYklGScA09kC71wi08T8s9ZZNIDpniopsC7Kik3nC4yz5ErRqIZM55giKjNEJmQ8dF1HrhGSW/sNb2zVPP9cn790+QIXtlb4ze/e5r/43m1+68Yh/+N31vnqi0M2Cs16v88rF87y979791RzOpAaCThrmS9qjHUMVY+rK5s0h09o2hrnHVJASYFXnlwoelmfxlpMaMicQMto1BGKr3/zPR4/2eNnv/Q2L1y9zD/RngcPHpNrwfhwgQwZXjiECly5fJkv/dLPcf7CNXrVINZxGkt/MML7mMus+j2cdTR1gxSSvMhxCSqXUmCaJkHA0TgLGe9Dr9fHOUfbNMgsHpFVUVH1+0itOXvuAufOnuPD8S2Cd1jrqU2ks0+nM6oyZ6VZ/BQrNqZkdNAooZEix6MhNFEYmHjLO4QpPiWmA6K4d3cmdMZNxv0MJyI2CEtN2HDivE2GRngIqQA75eri+8RYNr5/NETdCIgUTHSfoovAPMdoUPdeYgk3RvKaOvE8kQxjoBMwkKl0oTs5Pm08k0GTIlBKG6mtwZMJlkoWmVZkOrIgvbcEFw/X1nmUU3gX69OCD/TKHJVlOO+RSLJcE6vg4wfpOA5LCvfSMKfJXRbTpJvqLN4Z5q2lsSFW+otYNtC2ltY55rM5Kx4yrXA+0BqzTAp3zBqd/AgpJTpTaKkio8jZxPhxUfyUgHctxhim8wWCwMHBeLlZnnWEAFtbW+w8OqBpmugxeh8NQQhIEaNHpSNzbrmGujxaorbLZa4q3fY0h1II7t17wN/87/8ueZEfC5GGyLAsipKiKCjKnKoo6Fc9ev0evV6Pqt+jV8Xve1UVSR9FQVlWycBG4oUQguAc/eGQqifJ8xyZZQSZmI76BNNxiSt3WH9nkk8mi+N6C8tNdvpxfyZAZzgpmC9qrG0j8UdqMh2V9K1pqVtDr9RY56JWpXXJI5XMm5oqJUsdYIyhbQ3j2ZyqyMlVhg2xuLppG3b2nvL06R7jyZjGmDjXStEbDPDWkRU5RZ6zMhwx6PfRWtPv9SLl20UyyKxpaKSkLHKMizlPFzxta5ktakSWL8VivVAcWvhod87qzh6b5+CXXqh4cetl/uD2Rf7Rdz7kP/qnj/j7Nw75tz+/zheek4yKnCo/3dyWneq/0lgbWwQ5LwiNpx8GZDo6PWVWUKiSRb2gyisWtmF3eoAUnpxAv1TsTSIqMZ9NsM06ayvrrI1GNDU83Z5wfmuDc1ubKJ0T8Fx/7jpvvfkWm2cuMJ3OOTw8JM80RVkmZRWPtymNIBU610hkym/G1WRM3FNdoXss/NcYY2POLUShaYhLsm5qFm1DkecMh0PeeP11bnx4MypYWIdpavYODijzgC4vc/7y86dfsEKgRJSykxKE1PEcSvBMdCgF+I4s0jm4nbnoYrRYxtORAsLSEp6AKZf0+PTCS1RGE4LEe7mMyrqoKip3JASsu+QTxixGl7A8yJcf60SwIjhhFLtecmJ5PXH/SyQZdHXLf6w5e0aDFkKkDHsfm9w5HenLWkrwGuE16Fi9FTX7JFqLiAMrgZYQhEAFhzcxVR6EwNquWV+CzYgwY3d2xw/X5YeOK8gDKRQN0RspVIwgvfeYFIWJEJUYQiJztE0knQTvscf3OkJooSv+S4ZACnKtkHicNbQ2boCQosLZbMG8MRR5Bkr9sZP9acN7z/rKGlIRi059LOrUOks6fAJrXHQYlE4tWtJ1dx5Oorl2Xk03ujnzeHSmo7gucSG5AM4EjGuZLUyCGxIkkF7GJ+iiI+8oKSirkn/33/lfsr62ChB7teFojUEXQ6QWyKwgy3OCiCKrXcF9F/ElOfnkFC5jbrptKYmb5icpa//zjBDgoPYQdIQWrSGTCiUERjqMMwgnMMFjrGFU5MytpbF22c7FOBe1FWWLUwobPE3TMJvXzBbRoamLkrppePTkCXfu38U6A0EwnowRAUarK6ytjFhZWSUvS/b292nahno+Q8lI5lnM50mM1yGVwpqW1keou8xz8PFAXjQtjbWUWYFpZ7Teo0VklN46Mpy5u8u9nQkXzq1w/syI/9HrfV7bfIN//ME5/tkHH/Pv/4Mdfunlln/7yxdOXWwykZZqBAf7DQHPZDahKHIyOaRSfR6NH1DpjEpVUb5JWMazKa1p6cuc8WzKsFQ8f2HI+KMDNJEmX9c1s+mMw3HFkyeHDIcrvPH6G5zZvMDm1pkon5blWOvZ392FEPDO4GRqDZMXCBUPSJFYwd55HPGMsdahlYpIjnNkyZBBbKSZ5Zq2jUQpraMhJAR0nsX75BxN2/LKy6+g1N9JsmSeIBSj9Q2++Eu/yuVrLyH16ZVCIGkbhi7tkPqG+Vh2EzdNpFAtFWSI7MJuD4kT6aAlokKXKoJjun4nHSGI1W5p/8vutylhEXz84kSpRwiJhPIjUGYynB29vwtAYkwilvt9edwmXkV0bLvPHo1xPPt1RPViKPEvLkLzPrCYRyzctRKT4CStNM4qgs4IKkKLLkE4goBTEi0VTSo8NTYpICTjobr+ToilFU+3BSEFpm4o84zgPU/HM5wLiNagy5yVQYnuYKsQITPro8aaS56/DzEZTZJf8ohYdLjEnRMRolN4RxBmE9CaWSJnHD8mRk/BO+rW0NYN1lgWi2ZJInnW4ZyjKCp6vZymrpNiiKFIwqhKqWQ0yvh9F47TLZ4EDZLw8NSsr1O0J4TYaiRE0kKXN/AdzTewXDBSJemmdBf0UuGjk+SKxkrrLOaBgsO5FiEkVa9P3TbUtWfv0HHu7GZUTRBdri55g7Gafgm1dU5MF4wJRNw74vTF6t3wAbJCE+qQonuwzjBtohEOSDKpMNaigEG/x87hUXJcoju1aA3T6QxnLVmWYYxjOp8zns9iGUq/z+Pdp/zwxgfMJhN8iOt8fXWN0WiENy1l1WNtbZXNrbN89NFH3Lj5ESDo9Sr6vaj277sNHaeBLM9YGa7Q6w+xlcf72MfLmjZ2H5YCYy2tzBFKYlA8bjyHxjMQhnfff8ztR4e8dv0Mz68Fzn5uwGvn3+Lv/3CHrz9+wjf/m5scTk5HL1eF5vJzZziabDNfLDgYj6mqPoNeTk5BbnsYWzP2Ux7On+KNRQkILVRVQRkKJuOG2WTBIA8cHe5S9HrM5gu+/s3vcObXfpGNzS362QZXLj1Hb7hOUZY455iM9/DOk+cKpSJZSusclWcEQVL4SJJiUqR2PnHNZZnGu6jVqIMny/PYziepXwgiRb/X71Ev6mX9niDWgOZ5wd7+EbfuP8F4QZlnvPbaq3z5y1/m82+/Q28wom5aZHP6HBqwhPNBo1Rn3AzRoMBxQXIXtiWlECDhVizp+D4VLHdF1h26CEt0qvuDSAYGoSK7PLjIdOx24nJDdsYqdYhI7y2XhuyTXPRO0qpDkULHbkcsay/FCRUiH1xsvprOiVwJNODCT8ZrnsmgHR1N+M3f/F1WV1Yoi4L1zS2KsoDgKTLJma0tsjwjinmq1NxQkKmkCWgNt28/oigLpBA82RvTWEdRZknhPda1nYyMpQgoRGTaOcd8UbM126UvMvbXz/KVd15i0MtjHk6K2ImXpIvnu9xmyv2luqwQokCrSwWtUQTXY+uG+XSCzUr2d/fYOLOJmtfUTYsLMJ3NOTw8YlHPaeuGpjXMJhMCknm9YDw+HQXaGkvwkrW1VabjGtO2n4AvowRSC0SYL44lqH3i++PHn1zY8duOEhtxdh9id9lAQPpAkOkZSdQ4iFTf1oEEnTESYil5Fn+UOOeP3zNEnb9Hj46Qss/GVk5ZDY9zcZ1iSHqtpdcWWDIaO9JoXLjyp0IcWw8PDqY4EQtpsyKnbRtsMHjn6WUZudaM+oPkjXqcbehliqAq5jayOsfTKdY5tNY0bctsEXMkvUGfWbPgxgfvc/nyeYa957n/4AlaSVZXRhR5QdXrERB41/LgwQNu3b1LU8eI2LSG8dEE7zt6dqeUHnfuI/mIlZURZ89e4MzmJkJEuNOmw6k1Fsoc6w3eOBbBcX+a8dKKQgXLeG/Mb+5MeOHKOq9cWuVL5xZc6a3y4e6Qf/SdG3z8YPdU8+q8Z1KPKUoFTjCf1ywWNbN5xvpKj55b44f3PkDpI4SXmMaiUWihad2Upo0Qkzee+cQgisCTRw+QWQUh8Lk3X+WX/8Sf5OHH77OoDS4cMZ8eURUFuc6QuUBphRA66R7KGH1lkbiU6yxSyglYa5dF7oEQkY8QVVncoibLNFpnEeJSCmsdxhiKooirX0qCENx98JRv/OAbvPvDmwQz5dd+7df48hc/z/lz59BKU5S9JEwsT+3cQrfjYl2k1lGiLgSTiBexPkyIAL6TiQuRfXicsqKr11rqN4bOVTrOu3UOG3RBU6olS9A63qNDjEpjOthHpidh+XWyJizKVZ0wsohP5vqWkeJxBLI8xWQXaR53GCEIZPDo4JgujrB+Rmv9spzlx41nMmht0/DxjVsoqQDPaG2Tst+jWcwRwXPh0mVefOUFhqPYx0gmqEkrRaYkOMP3P7xFCJJMweRwjPWxe3KXCJQi5rEGgzXqeoFrFhR5hnEWEmV60cy4NFpj/+CQvfEMkeWIYNES6qMx+wf7DAZDqqqXIpWAbRqMVgmCi52DbUrSN63h++/f4OGTHZ7u7bM6GnDp0kXarGAxnSAFDFdXuf94l/l4j9FwSJnn0TD2+iwaAyo7tdCrc5amMayvrXG0/4CmbZdq811tHsESQiLOCLnMHy69rQBLhhLHOPUx+ygu7tgINC1sOrpNkp0igCM2kJQC4QVB+ghnnmBmRJGLY2Fhmwg53TUb49g/mLOytqAox7GVTNlbQg2QmFMpWaykXNplkTZBVGD50eKLZx8HjWfFZwRvohPjYg3eqOhRVBVSKGpjaVsDIlLwL53ZpMhyFnXD4/3DCJ0C1lmElPTKkqoq0UJSaMndvUesDnKuZpK1+YTNzU0eCZjVC1yIKiFV2aMJcPvuHSbjSdJxDIhU7iKkINh05IikGhI8Bmh295nO5kgpGI1GBB8odcZB8IjWUBQlVRabirbWsT13XOuZWFaTSXIt+M6He3zr7hG/8voZzq9nrJWWy8VFPnpwusLq+azl3W89JFcVVTXAGMPh0SErgxLrAoNiiG82ONo7xFlLwGKaRSSJiVgk7nw6uIQgk5YQGkwLT55s8/0fvM9Xv/gm0+0HlEWG1oKq14+sz7xAax2JTCoSn2Rq6RNrBFk6XjbJhgU6eb7YOFeRdGZ17EKupIztf4Qiz7N4Xc6Bknz/wwd8/XsfcPfBE166fom/8ud+hReunKPfryITOp3RHbrQNW79qUboMkYRoYkkPBcZ5sikmp+Egrt8VBeJCY7zaqKLgLo82wn294lr7BCepZZu+m+ke3jjkJyI7j7BPD5mQHYo2Scd0JQOSdcgl3s9lQ91jrCIKFGM4iKKhJAoASso8qwizzVSu594zj5bDs0HvHGgJR7N9oP79IZDtFIoLblz6xbjg3021/uRhRUCZa+XIDpDmRXUtWcyb+KkCZm05mJuR6Sk4Fqv4sxwxMePH+J1hpAK50Cg8NJzUIwY6orGOW7uHPHYCOrJFDnZp20WPHz4iLppuHDuLOsbm3hnwQWkznBE7zIvSobDPqa13L59n69/5zssFovYTt5t8eLLLzCbzSDE1gmBuOj7/R6j0TAmRdUCLxSWBu35xKH/TPNKYD6fMRytgHwQKdtJiDbP4y2SMiQvPh1+rgvqTyqgxI0bj0oPQXLSUfT4hFVz4vdi+RVCbCFBAFznJQWiCCR0qgIxLXfCOLnoaTmXxJpdlKrZPzjg0tVXEGqARxE8sdYuGHplRQjRSHjvGQ6Hy6hsSQIKx1d32mFS/UzbmljYm+fIMnbRFkhmzZxmUeN9YKUsKMuSV154nkFZsr13wJOjKcYaXrp2jc2NddZXVynyDA/MZ3O+/a2v8cPvf0BZ5GhZMtI5f9pJrgwH/LW7N5iblo21VfKs5PDokCePd7Amln6sra9SFQW1aWmbBpNq/rz3BNdF1wLhHbPpnA8//IgvfuELrKwOebKzg0cwyiWZznjuymUypTiazZkf7eGlQAvJzEt25Qr15bM82j3g//77D/ilawN+8eVNnn+uz7B3utY83kHTapwWlFXMo05mUx7vPKVXlQhvuXB+ixv3FFK2BN+QC7Mk2QVitCuVphCW61cucO78eX7/uzdp6gUffnSLP/ev/QovvPkO091HqCxbdj0PIeqfBg9a5wiponCv9bSmBRHzvChBrjK8j3224mEpKbMcKSWLusZZQ6azpTGyxlKUJdu7Y35w8wHv3bzDZDrji288z1/41S9z8fw5hIC2XsQcv3fkebGs3YxoikvyaD/FEF35h0BJzRJGFJGmH2R0epaUYHGcPogjFuyHBAd2J0SX61qiIF0+awk9iiWuY0PgyfyAzWIFmyLAhGEuX+PHBqJdTrzjPXSqJp0CCJ06SIoEhaBDYqLSSNf3BpzS7JgmqjgtI79Pd3Ofmbav8Pi2JjhYX1lF5Zq2nuO8wrsF24f7PHp/SrAtRVkRtESXFUppLp4/y6OZAalYHQ65eu0Fzp47G7Xuyl702s0CXVQcPrxDXk/IlaD0Ktpu2zKu4dLmJudWeti9Xd7//gdo7ZhN5qh2QiYk1lryXo+dJ0+5e/8RR5MJa1pRSEm1tsbCQu0sZzY3aNqWvb1Dnty7jzMtZ69cYXf/gL/7D36b119/nfW1NTRRYZ0Qc3PGx2ymC7Gbc4TfT3/sSqlYLBpW1/oUZUbTNDibINE8Bzxaxs2mVPQAj/N/EDGGY88r4SRLsdWuqWQsiyclc9OCCwkz5wReEVcWUasSlkSZTh5UiCXFGaLeoGkNTRt7ujWtYfPsNd5654v0+yvE/JBlfLTPwe4TRisVK6MoDFtQsL+3R3Kvl1DpJ/lMp5/bmBcV9PtDhFQYZ6jbFu0VWmqccbRJxkxkPS5fvMTnvvAVdJYhP/6Y5rvvIgRM5wtWh5bZfM5k4pgsanb39/nm+x9jjKFflgxGK3ip+Dt7h/x7fsAbIucfHewxm8zY2tpi+8kOpo1R3vkLZzl/4RzT8Rg7c2hd0jaW8WQSJbE6jze5/wGYz2e89/77vPryK7TWIYAzwwwTAm++9TmKLOPho4fcvGk4kp6JGrHjSw7rhnxuyPpDMnGV39+b8+7v3edfezWqaZxqSIXur6GzXiRk4CND0EbFm0Jrrm6tcG/XMp1MYxSVdfnbqDhU5Tkr/YoLmwPObK2xtrLCz7wW+MMf3OXh48fce/CYl66/yt3ZmCJXSJmBEKkuTCA0uJCEHYIgKEmhy+V9b1qDc5Ysy3EhXp8zhqrXp6qKGImpqI+ppMS5wJO9Md9877u8e+M2Ugh+/vOv8Parz7GxOorr2DusdVjno36rSBJmxHPZ+4T8nJLxvFy3IZU9IVL0GQ8aD8mQkUqWujYx6pjFGXHIE+f+sdGCYyMUDZJf5qmOof54DngczpPk+GL+povG/Ak5rR9n1DrHtMudQUKaluFsLEVaEkQ6Y+Xj9zIkfajU+UOksgO/NKo/fjyjQbP45glBRthgPj2MxYZKoXQZE7OZQPaHEfdVAq/Eso6gNQcoLFrk9LOK3M94dPMHbKyvcffuA4Zlj4PZPkYGcA7hWkZlQVmMuLpxnVxmrJzd5MxWj1Ffc/7eA/7xH3yDg90j8JD7moPZnPVzWwyHGq0UA1lEBWwFZVHgdEaeQSFy6kSR994zGPQQIeb2prM5UitM66gXDTJYhon1FunaMZFu29juxXqXepk902wuh5QS0xqCh8Ggx3waqeXWGQRV9J6kwCQtOiUVDrtcr8e6GmnBLJmELIksXXnCJwoZ08ZY2rAIvqS6lKhYsVw6S6MYUu4i+Y9B0LYNs9mEuqkZrW7x2ts/y9ra2fh472nrBfs7j5jNx3hnefrkKfs7eyiteO76i6yMRmRapdrPBI0kCPWnyUUASKUoqx6tabHGRONrDV5I5qktfGwFD8J7Lpw5x3PPv8iZs+cR1ZDsN/4e4+mM/fERWkr6sx4uBPYPD7l19zaL+Yxh1UMrzY3bt+j3euzu7vF/m435Ny5e5Jt7O+xbExVffJR/OnNmi9deeRlnLLZuENMps3lNUzfLth8n2yix9Jxh/2Cf3d1t+lXOoKoY1WP2nOWVN95iZTRk5eZHHBwe8dHU0QZNfzSkkJOoatM2EcnJK9rhc/zX7z9lb3rKSEJIdLWByiocjsy0BG+Yzmt2dg+4fvkcPS04MypoLVizQCpJrjVVFrh26RybK33WRgMyBWfObJHpjK2zF7j95IjpYsHTnR1ef/Vl1s+cp1mMIUDTtgQfGPb7uHDcCDbI2O0AAq2Jj9FSU5YFCMFkPEPrWDYRnGM+X7CxtoINgrpt+eDOE37vG+9x/9Eu1y5t8j//87/E2sqAqiyjoXIu5a8FTROL7q0zFEVG09QIwHp3LCLwUw6ZnNMoCK6JDOZ4rzqjFXNgqXu679Tzu+gmHBu1cKyreKyK1EU7J26pSHmy0Bk4kfgGHNP3Sa+doMbjiOmEkUnn1fHPXaT2R1Gl5emVrjFxRmI6IsQ8olApspYZQajYgeBTxrMZNBEn2oeAT3URUbA2qiY0wSGFRskcnRfoIJGpyFEKwaQN6NT2e/9wm/3DJ7Ew+Z6M6uNCoVWsU4rQliOThjf9i/CNXRaTBTurT7C/8BLN5ZLbdx6zs73Hux9+zOUr53BrIIqcsZ8y3Z9GVl2QOO8IUiDanLz0FHmPPCsISFywzJoWlWlW1jY5OJxijYlq9Trjwd1HOL9g49wFrHdR4LSpAUFjDMbGwkr304iRpiRyYxyroxFHh9sY0+KDXbY1RwSca/C+TPCsWnaMPWHOYHkQypTnihGaVkm8NNF4SRsiCGJngSW27hLoIKNXFGIB/XECOPZI40R+7mgyYWECL772M1y9+iJKx35u3lkOn+6x+/QxztRAQCrF2XNb9KqK737nXV548Rr9qkKpgJAaUnfajjnl3E+m6f5xw/vAYtHQ2AZCzJ95AjbEHnad6kKndjOpaz6+fYv9g0OePHxAr+qxs3vA3t4BZzc2qYqC3cN97t+/z5PHj9laX+dn3nyLsj/g1u1b3Htwl16/YkcEfreZsdLrcTAZEwunFaPRkC994XMMej3a1uCCY39yFOcm5RNddyglQwYnawxh58kjLp/d5MzFqwx2D9mdG+b1gqoqEVpT9Com+/uMVkdsbm5S5nlq7RIbU4KIjTE3ztCK0zVPFVKjixVGwx4bqwMOHiwwi0OatmVR1yzqllY6Xjg34LARNK2iX+Xk0vKzn3+N569cRIRApqPDm+lsWabz/JWLfPO9OxyNJ0znc8rhJvPpEQIo8oIAGBfznZ0STpZlydnT9AcDRIpsYlNTx5myQgrY2z9gfSWmDBat47sfPuAPvvku49mcF6+e59/9y3+CsxsrDPs9msbgA6mfXySLhGAReIz19Pu9xJqNEVqmM0KI5RNK/3RGrTv2fZJci6iLSnB/2qedU4lMCvwQdRP9iRcJy29jnurHg/jdQ+UJCmTUg3WRNBcMAZeiuhPRWZe3616ngxI74xSOI774eNIZ1dH0u/WUripFdct8nMrwQaPICcQu4ic7u//oeKbVXJQDzl18g9lkjBQhKU1kuOVhekJtS0QVCK2jBNJwdYO8Xy2jAq0yYpTg06LzGGMgHAseCwEvbl3gyXeeIscNs7rGzo84eg/m4iI/vHGb3voaL77yMlWvYrQyQCqFUt2Exg+eV2XydFWCBkRiOEqEKDhQORJQ3uCtxTRN7G/lDNYZ6raOizYEFos6itEiWTSGum5p2ja2ZD+l9FVdL3jy+DGjUZ/BYEAIj3DWUebFcmFHL8ext7vD+vowIYLJ0BCWxdVLuC4xCr2Lfba0jt5lpOonkWORQvylUkBSB0F2yjcsddiSAUOQlDFCMjqC9a2LvPDa5ymrQXyODyxmEx4/uMt0ehAdirS4VWqZcvv2HZQWHBweMJ9NKbtmoJlGqyzeRxk197ou2acZAnDBYVNhfCCkvEJSViCyuAKRDfd075B7Dx6x/eQpj59us3dwgFKSL7/zOlsb67z3/g1+8OGHjIYjrly8yObGBk/399hSipXRCtevv8D+3gHDQZ8FYPs9eiZGaFIJLl44z7A/IIRAkeVcuXCJ4OCjpmUaZkjrUSEsI7XkWuBFoGuMO69bsrLP/fsPsEWJlZ4bH37EaDDg6PCQRV1TL2p0NmVnm3RwCIoypy8qJrMp0+mMuq1PjSoIoRiN+nzu1esMBxW3VcODm+9hTMNsvmD/4IDRoOLMxoBXrhQMVla5eHaTMlP0slhjVxY5ZVGgs5zgPXkZy0Heeu1lvvneXR49fsze3i5ba6tkWY5pa9okCi6VpD/oJ8q+wibHJzKaAzpTqDyq4Pjgmc9mKCnJi5K98Zyvv3uLD+88xLvAz7x+jXdefZ6Ntagy4lMT17woU56sQwoEbdPgCPT7/ZRvK+j3K4xplnWjxrTMJs2p1yxAUDKW2iCT9mGi6fsutpGpRjSBLEuYMdXFdY7aCbixi5JOGqRlDq2LmkR0sEMX2YWAc4LgRDKWcc8cy29150JXRtAJVXT5vO59Y+2fSAe7xyOXZ5ZIaFDKp6XfBzIUkno252/9vb/N0dE+Unh29z6dyPRMBk3hmO8+om4F1XBIUGUsLJWxO7LoPHcRVRiCkpFEIgLh8BA1m0dmUZZRlAUqy8nziqwsyYsiqXtE6aw8z9DeolrPu64hKwITbxDS84o0DI7GrKgcl40oX7y8fE0tk1hU6A7meFhFogLYtiUEh63b1EbeM5tOybIMnRWEMMXWNXlZJDmn6J05H3Aejo7GtE2DkJq2MRjjaNuoGnJaLceyLAneMxlPWF07y5Url7hy+Qpnz29weDDBtNHoK+W4dfsjrLnKmTPrkDwmYKnUvHTqk6fkUqlClmUxWvOxDCxGXLFeLepWkiJwtVzMXWJ56dGJTvcxutJexAjq8tUXyYpeMlaBJw/u8PD+LZxpOC7PjBbSWcuNH96lbmpeevk5YtSml3BmVPy3dAoDMS/xU+QjkkPqnEtF9sftQTrnSqbDwxNojGF/b59eWTCbzvDesTHqM58v+K0ffo0QAsaBkgrjo5bh+sYat+7c5ebHt/HesbmxwcbmBsE5rl27xrmmYTqbEkJgbXUlGtlUtF2VFdeuXqZuFtx9GAlBIRk0F/zS2ZbwiYPNBEFwlie+jxeOne0nTI961HVN0xiCM7RtS90Y8kzjA4zHE/I81joORyvkoROaffaRackvf/ENrl48h7WOyWTM9v1bNM08IhdOoHXFZFbz8oVzrGyeoyiy1FlCggg0jaG1liwvqPoDZKpHXR31EEKwmC+o53PE+nqMCLOMKsujjqWPyENrWha1Sw5rJEpYa8iLnL6EMs/JdM4szPnhzYf8g699h+m85sz6kF/7ube5fvks/bI8URsZlvO8jH+kiLCf9EglEmoQyJSkWSyoiQQRZx1N2zAaDsnz0xdWd1B/XPUBoTr2oUgNPTtUMSz7B0bZKZYdnrt2mCIp9p80QJ8kr51kMMfHeI7JJ87HcinrzLGRPJGfC/xR43gSXuxKJ2LTxhORV/fY5WVEo9hFiiLpUwohaYzh9vvf4x/+7d+gns7YefzkU+fu2Wj7bYvUBUePH3H09ClrFy4w3d+nHI2iEnnq2SQAKWw6ZOMBuKjb+Jh02CJjO5LjanCxPIS7ZOJG2eOXNl/m5+c5rrYYN8DqgHhas7v3IT+4+QFtr8TIwOrWJjYkSDP1jepqngKpQFgdF+qFQNLWiwxDlMJJHZ0DpWm9x3rHpSuXaetJxOsD0bDkBUJoNBovTVRZT4WbpxkhwNr6OkIorAtcPH+W0TDHtDO8b5EqYzo+4Nbtj5GiT15kiaEUc5ORxSQSzh4pt103hDa1Ts/ybOk9dXCeWNL8ZdIUjInoblMvWU/hmEbewRIdTG9MG2ERbRBoEIrJ0WHsTSXiOo5lB3Hxt2bMysoRL555nizrRyHY9H6xEF8m7D5uU9d1EP8pRvAhiZ0SIQtPjNZS7ixGm9FUGGs4mkwxpmU6n9HUNZc3Nrj38BFCwHxRs7oyonWOwWDE3v4+ddMwnU+xSZ3i3PlznN06w97eHrP5grNntth+dzv22nKRcdlBVPtHR2SZ4tq1q0ilePj4EXVdQ4jFvq11S9JBt2+E80xnU/KsYN7UlL0++0cTrAvLKMU4h5vPWNQto9UR1lqU1AgEOo/Sc1tr6xGKPsVYHfW5eHaLRROh3Befu8rs4DHvfW8fbyz7hweM+iU+VzTzCZIthIxsQKWi99RLuqJCxLSA8FAUBVmRR36A8+RZRlFW+OEI08zwzjGbzci1wvjY3VulNk7OWqqqwrSSPMvBw9P9Me/efMjXv/s+3jS88fIVXnv+MuurA6qiSJ8mogDeB4oip2kiq9kRz5MIgwXwqQQgQcMoUFmEydumwTpHr6xSGuL0LEdv3JK8JYJHyhKhNBJLUKkzgIuIkxCO4FNXChmW+SrhYwQXF0RssMxy3yaJjs6YLQ3RcScOuZQXjO2rnLNp+aXzQJDU65LTm3qciSRndww7HqN3aSKjmRUn6uK6x8iOBZnILRJkFjtcDPoDbNOymMw/QUj50fFMBs20lkf3HkXPXkoOnz5FaR3FP5WNBkPG4kQtPUhFkPFDKxUbTB6TkT+J63aLJMs0rYtFl/vTOYd1n1JJ7GJGEyxzazh67zY7TJmsaNp2zuHjbYIUqKpESYVUMm5eoeKNRGJVp/6e7lMKp0UQzGcLjJmjq4qQiitjPywbhZWzPLWYiK06srxCSE2QBiNEFFk2p48iugO1aRrqWU2VCR48uM3B3j6LuqGuZ9jW8fqb71AN1tG6t2zXA+I4AZsWYyzh6FiO0SDkiapsU2SwlM8SHqmyVDMIS1VsqVKfus5TS15e8ppidONSQj7RgyUQfGx308EdQkBqyR7rUEp8KMnEDlUxx4QLSJEn7+y4vU30BJNn/GMw/2ea305UOcSCcS+j5BeJLUdqG6OkIssKdMpROh9QSrO+vsb+0YydvYf0+n2sczx68JCXXrxO3dQ8fPwYheDatStcvnQZZyyT6ZRFvWC2mLN384BH29t4Ys7SBUeR54gAs/mMxXzO1tYZrly6DAT2Dw4iiaVuCdTES43zLwGdaYxzDIclk709xm2DbS/SLGLdjiDQKwqaICl7FZnOqPIS1zpciCzLLNc0bf3j0in/XCPqeAYGVUaR54TgeP21V7l18wPaxZy6jR59nhc0dY2p54zW1sl1RpbFOi+pFKZtY5+5XEenSkoePTmgrWtGwwFHRxPm8xnGGBbzGTrVntkAWkboXKX8sHeRiSd1zkcPdvjO+3e5v73P2Y0Rv/j553nx6gX6VYlSeunkhrTWCQGtwCRIUwhSA1xo6oYi11hrCEvd2lgb2x2uXc80iPv4lL7tchwrzgt6/YpXP/d5cDWQpbZa8QSVAkituToDFQW/ZUpD+NRkRMRIj3jfZNpvMTBVCBmQQqGEjgGBil3sdRFzlmfOnefP/Zt/MZVgpdyaCwn1SUpKweG7A1ZEo2lTd/Tgj2uMfThmM5Pg9C7sjBGihRRjnr9+Ha0V3pqluv9PGs9IChEgNDJTIGPRNFoRpI5eeooAcJ7WeYSIVt1LiZOGTuooVrqrWKAtojfZpXS6KCqEQOM9H+1+zPX+Fot6yp6tOZwfMQ4Nj/Oacepl1DrD4d4+ea9CSJlaRujUaTbKXXVfcR7j5PngESHW0PSHQ5pFjUk1YGWvoijLZQdbn1rKNCbCjEJHjT9nYyNIk3Jspxmdw2St5+GDR9y+uU+vX/Hyy6+xsjJiujAUeQ9rLd5aarugrCKkIdJCTq9Eh4bHpZI6CTgXxYEVeOsQ+Jg/Smwm4w3C22WOBhWjgGVzus7jSpCmSlp4oaMMJ3KF911NyXFur8P5ffoSQqLECoezHkVpGPQeYsWLy9foNmaHpR/nBk83QgCbWgEt5XlwdPwsn5haEWaR5JmiLAqklNRNQ1HkUUVEZjx6usPO9jbDlVUQMJvX7O3t06S8qneOXlHwwzu3qXp95vMZ3nt2d/dp6hYtJfPZlNm0otqIiMK8adjZ20Vrzbnz5zmzeQYQtG3NbDrHHFmCF1jskpSjMs1ivkBvnKHIMibzGbPFgiLLsfiUM82xHkzT8HQ6YXW0gvcW4yxZXqKlwtrYQeCUM0uvUpRlHlV+jGVzY5Vz585y78496tbw4MlTXur16fVyHt6/y9bZC0vnREpJrjTlsMR5T2sMK8Mhe+MZv/3736Y/KKnKkqODfcYHa/QyiVaxfhBEJI+ldWm9w1jPo91Dbtx5n9sPnpJlmldfvMKf+oW32Rj2MKalX/Xi/Rbx/YWMEm/WWjKtsc5GBEJKlFZY6+OeC4HWeXRRIonSd7PFgl5ZUrc1WuslgckFT1GWpxZZgLhHXdJtDMDGxgZ/6X/2v4hM3JTrjjkzF/ui+UDoDIx3kKS82nnLbD6N0nQSBlWf4CUimLT6FSL4FBEJRIiEvU6ZP0rlgZeBqurx0quvxj1JWLagEiH2Aol5fJkEi2VqeyM4OtyjtpDlBWurQ4TUCKXje6tOqFykwIaYnuqiRiEIQtIu5lFYY7lr/wVFaJ0FDS4xBnxIHlFACUWm8lhc6znuf5Uiha5zcUCCSIWtqb+WUm4JK3XMOS1jEfXH2YK9ez9kMZmxkAFfKGa9jHmmoh6byiiGK2RlidIqhq9KLVUEVNKbXB7WUoEjNloU0TNbO3uGxXzGeO8A27a8/rnPc/3lV5FSs5hOIjU/QT+L6Yw8z1FZjjWW1jhM3dI27TKR/6xjOm+YNzDsKbQa8MprL7CxscJ0OuHGRzfQasSFy1fJ8kiqscbjXaej1lXwJ/hWnFCfEIEQ4twWRcm1a1e4d+8BTdPgE5sw3tS4oJ2MHaKFC1EhhNR0bwkHJ4/qRIlCjFw7jD56lC741MlWLJdJhGwjxaFtHD5M6ffP0Ku2wR9iTXYcocm4kE/06T31CIkxGEsIHMFGSZ9lLJqgTZ0+n7EOGxyYWHPWL4tkmgPXr1zlGztPkd5zcWONt69fZW/vgN3WkJU5q8MhQy2oFzWZzvHWMp5OWNQ1mVbkZUHTGg4mU0YrqyghKbOMtm158OQJg1FU3t9wNrU80bSmRbQ1YRFw3iKEJ5MRbcgyzWDQZ1bPadqW2hhUgt4a29Ik4q1rW/YOD9FKkRc51iy4d/+I+Wx26nmVAvqFjpqSSbhWIXj77be5f+8+Migmi5rxdEqmFYOexruGldWzybHoHCUo8owsi3qa3/3BTcqqYGNtyGIx4dFDw/Vrl5FFFh0NJXHeJiUZmM5qbtx9zNe/9yFHkxnPXznLv/7Vz/PaC1cpqjKKitctuixxwScER+Fc7IcnU4mL97HYPWV7MTa2/tFa0StKPJ66rtFZFmHfPEvdOhTGGvK8IC9zRBKaPnVyMi3J4BNRwgXMfE4IHQIUUiG1IoQ2dhGwjqdP7oHM0dWAB3dvc//GTbLMMz44wprYqLfXr3j9c+9w6eIVev0h08kUgWBltML6xhZVOYgqJzJC/0pJdu5+xNXza0wmLdP5HOscZZHT60XlH5f6IrbG8N4H7zOeLzDWsru9w/s/+GG0D1nGyuYG6+c2aBrDfLKI0oiZYrA2ZGVlg/WNs+ADj588RCroDdaoql7slCACQks2zp/DeYHYOfjUuXs2pRDiZhFLY5US/mlBzI2h653lU65KpAmKLC+9JAAcU2BJebZocHSy2IGA8pK6J3l0vmIiJ3jrGa1qFjoWRGqdo3SOzHSEMZRatp1RoivKi9ZfJcgxIECFGGYnaEsCV1+4SD2fc7j7lOsvvUyel7RNS9M0NNMpZX+EWdTs3r3DfO8pOs8JqYjb2dg7KZySvOB8wLk+SlsEkqe7R2gVePjwIT/8wQ95480vRfVvlQFJEsoLhOoC95SkXUIRGjiOiL2LDLK/9Jf+IqZt2d/b48GjJ9y/94DtnR0OD6e0rTlmPhK1HknNQLt56oxmZ9BCghe9N5GhSpzz4EIyZiImqBMs4VK0+2Rnl42NARLY3m2R3GGyqFldXWV1dZWqKmIRLV3N3E/h7XqfIsoIlwYRcyPdOkFG+LRTIjDWslhEj3beLCiznLptyXTGxmrJz/7sz/J0b58H925xOJ5y5colVKEZViVXz51jYRwehwmO/mDIvLEMV1SEGEWEYXtlhfeBo9mYR9tPUjH6lO3dHaoLEXZ0IZDlOYPhCFlnmPYAYyMUpbKM8+cuUGQ5nXqoaaNTpbVKDMeCSgucDyxsLByXStFaQzOvUUpQVNVPRbix3kCICvZSxdTCpfPnWF1b5WBvH+c9B+Mxg15JnsHtjz9g6+wFeoMV5vNUVoNcOlyLtuX2/W2qQtMrVni6t4tre+SZTg1UYx1VawP3n+zz7ge3+fj+E/plxpsvXeHNF66yubFGnmlUFh0KnIs5uzT3IjlkUsbckNKKpmmxROKUTFJY1vlo5HygxaK0Ii+KuK5TN4zWtpRlRZVVKK1THRxLNOC0oxWSqbH0pKEsA1JmHIwbjA0UVZ9hf0RrPY2poyKKaTma7LFoW7a3n7B7cMh3v/F1tDccHY6X+bAr186Tfe5N7tz5iJdffY3rL11jbXUDa1qO9o+oFxOuXL3Oyvo6Uiqm4wkPPn6Pnb19VvpDrl29jNKaw4MjDvYOOH/hPGfPnWVldRjVUbAczWfUi4ZmPubjD9/H2ahR+srbbzEYFTzdfcrR3iGPbz1A5pLn3nyezc3zbKyukWUF/f4IlWlGoxWMabl35yZXr15n68J1fu2vnGN2dMCv/wf/8afO3TMXoZy8T877JYuGJEUTo4NAVxga+6JJDAGkQOs86a8lGoOKOS/Xtqg8R2odGYlx9yO8xSuJWBlRH+yjiJGZ0Apd5KysrUXF7UyTK40LITJyvENpjQwh3dCATFI7sdYpHgyRcCMxLuCsJy8rpkcTDp/eQpcF4/GU/UePePBgh/l4wmw8ZXJwiLMmGnYAH9BFFnNHpxiroxFvf/4d7t3+LpmSmDaWMOzt7ZPpMib5jaUsgBS1OOc+0a/JJxbhMV1WLNlyxlqktUyn8RDZ3DrHhYuX+NkvfxGCYLZYsL+/x872U55s7/D06T6HB0fMFjXWmdjGBbFUIgihK+RMMIuwuPkcrRt6veEyMosRfUhU6GgIm3qB0p7hcMCNG7fQ2nP10oQn24K9gxkrozkroyFlFWWOtJI/1aEbvd2w1MSM1xUXsVYqKsCo6PS6EKhNi5yOKfKcpm5ZKWKrEk80+JlSrAwG7A9W+N5HH/LSCy/w8nPP4V1gZi3ff+899vbHqKxkc32DquoxXyzYWFnhvQ/exyxqtjbXsdby+PEjnu7ukeWRLDWejFm0NYtFFLpeWV1jc2ODx4+fsH9wgHGOEBRZXnBucwuX+vQZE1VajDcIF6jbGlH0kFJQN3UMpwCcjaSLgUJlWSxS/ikOXmuiscgytWQXZ7ri5Zde4vd+73fJMs1svmA6m5FphZZznjy4zZUXXqPfK2laS6ZUbLYLPN7e5eGTJ2xtrvPcxXOMVoZ8dPMmf+tv/nf8mV/7U+weHPCdH37Mw50Dqlxz/swaf/XP/CwXz2yglaTqVWilCcTiZ+8dOhHVfAhkSqcIKqSehzrJy2VL5uCiackyjQiBsiq7ypaIPjgXITUhKIoSWUYyiFcK35qlkyTlsZLPqebVeULQOJ9x+949Hj54iMXx0qtvcfH6K7z33W9TSMmDJ3c5e+FirP2t1inEnLWRpBSSd4cDnj54ENd3yqlbG9BFSb+Ah/cfcOfmx2xsrPEX/s2/wtWLV3n08D6/8d//f6lry7Urz/Po8QMWs32++uWvUFZl7D6AxBrDxuY6Nz/+kN39Xc6fOUdZlkzGc3SmObe1yvbqBnHHxWi1rmecObvFa6+/yd7uPrfO3qBpFkztgsY5pvWCvso5d/YseZGTZSW37tzg8qWL3L55gwvXrpMpqPpFbBz8KeOZpa+Cj7mVGNkk9pqNLeyRKrGxSASMEw3oUrM35yMEJoUkK1MCXghUHr0ok9TNvbPk3vL8fEoQgu8Zjw41zg/QIiZ080zTK0vcss4qwhAygE0HKEBV5BA8bYjq5DKJo3YEEGsMWuZk1QCZl+zsPKU52KFXaJpQ4aVmNp1Rrq1zoaw42tlG5FFjMuYPWpTOOLj54akWcFUVIDRlfw3aI0IQ1I1jOBwyHTcxx9C2Jw72rjVOWOaF4q+7fNNx8jTgmU4OUVrT61UxyvYGYwNOxo4IVdXj8pU+V65dTa02wFrDfN4wm0zYPThge+cp+/uHHBwcMhr2lzk47z3WWyaH+xyM93jr7S/RXVEIAp+6HSTxbrTWXLt6hf29CbP5gqLqM114NtamTJsBrWk4OHKUdYVOBAJrT3/oCikQwUcZNgBno/hvSJ2SiQSZLNNoEctMQh6id06IBfhBkJdlLDnxMSe4trrOk+1HOGtYGcW6sodPHnN4dMTa6jrBB27ducvm2hprKyPuP7zPeDpldTTEtYabtz/m0eMdkJJcKKw1zMZTnu48ZXNji141ZDTqR7kuY7m//YjFoiEA58+fj+w6PJnKIMSo04coFE2AItfMW0fwhrZexL1b9dC9HlVZoUQs0Viy2Z5xSCkpypJMSZyzSAIq1Q++9dYbfOOb38C0Lc2JJqhFVrL96B6Xrr1APljF2FnMbSdI+9a9x9x78JCyUBweFQz6PVZX1/jwxvv89b/3u8wXDS9cO89f/rWvcOX8Bsa05EVGkRVx3+vorDZNnWpg9Yn8TILonUfq2GiYEI4ZeCktUemMuq7pVVV0EiFC1T5E7UkZRSAilB7iulCa4F3ck94vae+nHVmhObN5jg9vfI/bd+5x4fJFbn70EQ/ufMyDB/e5c/tDPvfmO1x77gWe7jxhfW0zli/M5ti2QeeaarSCaW+fQEoCAcXWuUv8F3/t16knE4oio6oK6tmc6XxBvZimIveCj27+kNFgiNYVdx8+wRM7pEshcd4wmc2pbeCb3/kmprVUVZ+NzQ0G/QGTgzGLWRPfGwFC8uKLr/Frv/inaUxDeEHxCz/3VebzQ379v/p1ynKAViX1Yo53LbotyPIWKwUXzl3n4cMn7I8POLO6xdXLl2L/zE8ZzxyhiS4vpiSmXpAVZeqBJo+BISWjgogP3XqKNbsi0ToTqcBbi0sJ2o4H4ENA5nmsDK/njNspC1HQ60t0OSIUA2SWoZWm1+tT9HosmjoW+wZwxqLzHFyEOQUCL3WEXFKCs6M22zYaC6U0jaux1sSkaBDo3hDnY6RYjYbMxxPGT5/imhrdK+kNV2nqGmdMgnMiDHqaEUL0dtfXz3K0M0Flirq2rK6O2NmeJBpwm5oTRmjW+ohfpwwagiXrNc5ld7+Q3H9wj/v3H3Dp0mUGwxWyPI95Imw8UKRGeoWUaX6ERAhFv99nOBhy9sIF3nhDIQVLI+qcx9iYfHbWgjPsPLqLe/1z0Dk6dNpvYRktCiTTac32zh5rG2sY49h+usYL1w4QEnTRx1tH0ywwtmFRi2UN4WmGEFF5ozWG4eoazc6T2HYjRAeMEKLuXlqoLtYlxO64Ke+rdWpom7xdrTWz2QQBFFlBmeccTKbcvHWLprF8/vMvopRkMpnyZGeb/f19qn6fjc0tpBCM53OOxhM2tzY5s7WFM5b9o0MODve59eA+m1tnWF1dITjHw4cPWVldoVBRym04GrKxspbo6jllVVHmJYrItnXBRiWUumY4XCXPMvp9g2lq8qKKhrOuI5NXytjv6lTzCv2qoMgjQ9U5h06CBmflFs899zw33n8f52EyXTCqKga9kul0xuHuNoNBbK3TMfJqa3jvg1tYZ7l7/wFVFiFBhOT1N17njZee5+LZdXq9iiIvcM6iZQEykhqE0tHIOBvzeUov6eAhxPIHmR1DzB0N0ZgWqfN4ftgI0xcpP0YiOuVZJGDFjuGk2tTYNgmSwYtQQKK2f1IU/FlHCIHdo0M+vHkLmeVMmoLxeMbF8xeprSfPS7Yfb2ONwLQhFtLXhtFwyG//zj/lYPcpR0f7eCAv8oQkBXb39/mv/l+/zvhwj8nhmOA9155/nkVruHL1Gmtr60ip2dnZZufJAw4O93jrzc9TKE1dNwwHfaTMUWQ45xjPFnzz2x/gXIv3UXPRB8diMWd7+zGtbaNMVfBsP3rED374Hiur6wz7Q4p+Sa56ZMBifsTj7TtcvfwS77zxBgdHe2zv7aI8fPu7X8fbFin6mHrGk8ftTxRaeMYTOC7YEDxVlbN1zbH/uMbbfmTSycRc8YHgWpy1yDxH5nFShY50WWvaWLvlbKxvUIosz1Prh4RzOwfW8FKv5n0q8tzSirMoXUSPSiuyqkcQiqKoiMIZUb9NZxrqBqUVWZbHHAkBZCCDRP+MsJkkJEpoLDNwKfI0KBoSvV3EQvK8qnA+qk74ENX7CbF2pp7PT63hZoylUJLBaINm+jh2124X9FdLVJZqvZzDmBatKrpWMM51dSFd8fMxfZ+UnBZ4qjLnoxsf8f5736csB1y5+hzXn3+ewXAY66KSRpyUAqXz1D0hFsD61CfNmEhF1qkTbwjRjDofiRRrZ8/zRlVFIeRUa0Lo1ssx2aeuax7ce8Tm1hZKChZtza0Huyzmnjdee8zMXKSqKrI8p1cVtKY90QPu2YdSmtY6kIZLz19lb2cn5qGSOowlQrd5npFlOZmUOGMxIhCcx/gQmb1CIlRq15EJev0Bzz93ncFgyHQ2o8wURV4isPRTburBg4coJWIPp/GYQa+iaVt29/cp8owzG+tkStMvSnpVj+FgiDWG2XzOw8cPEVKysbrOk50dGmMp8oyLFy5GEQApccCg1yfLMjKdoZTGesB7ZvMZs9ZSFSU+BAbDFZqmXkJrHkGhFLk85ckb7T4+RDJFUWQEF4UIVkYD3nn7LW68/wHWWmYLy7zu0Zg+YWq59/EHbGyeo+gPErHAsX805ebdewx7Ff1exaWLF1gdrdCalpdevMrz1y6Sq8iwiw1OIwFKSYXQWWTRmhYhBFmWpVx/R5QSVEWOsQ6VugGH1NAzL0oQibGd+v95T+rGoJdGDSnRucY6h2ktWQYhRfsekl6tRmt9AvY/5Zo1FiUc585f4tGTB7TzfV649hzWBcoq59Ll6xRZQdYveOn1l+npjO9/5zv8sz/8XYKb4+YT2tmUz331V1jZPBeJd9LjnUWKjMvCYI0nBBfZ3a3mwf1dPr55n8nhLs7EEqu6adje+S1ksDgbYimPzBAhstd39g55tP0YrQsGq+toXRKsRZRw/Y3Pcf2Vd3A+xDZKOvAP/unXyHXO1uYGWgkyYWnbFjefM+wPeeHaVSSSrfUtVlc2uLC5z/ZuzPE3tsXagFeCsig/de5OFVL4AM5NCPk2xVrJfLuM6sghJlI76EvmZTRmKmLSvmmS9BKgojq0znSECkTqJO08Qcf8XC/POZoLqmrOtljDC01wFplayuS9PlJrbGtS80W1TOpGzDiyobSO/dY6Fl70rlwycgLlJahYHG3bJtFhYzTiXEjUdLFUrddCYK1H5xmWqEJSDUfHObVnHJPJNMJZKqM/3GB/536aS0mvV9A2LcZY2rahLMpEXLU4F0sffHDLupcIKcbiXWM9WTFkfSNn89yEJzvbPHj0mP2DJ3x447vkeZ/z569w+fI1Ns9uUpZxoUS1DrM8HITs5GzkCRHU4y7fbdtSVP1P5KeWQxxL7pBIF6PVVZy3HOwf8YP3PmBlfZ1qvElrDnl0/wfMmox6sSBTBetraz9VnkdlGcXKOs3kkPrgkGow4Gh/Pxpkpen3Bpy5cJHhaAMz3kZnWaKCe2pjGBIPK080jpIAzrG+tkazyJnMpmR5wXwx563XXudgfERR5CghefutN9nb32U6X5ArRZVKQYxpKbIsilwLmDcN1sdcTlmWDPp98jyyH+ezKXXTkBcFa2vrnD97LtLEiWs8LyrKKrZoatoWoQQm1ddZ02IbQ1aVmPksdR+XZIVmNp+zmE/RnC7XI6WkLPKURxexHCRRr733PHf1Mr1+j8VsivOBummYzBZsrY1YLBbcu3ODqy+9w93HO7z70QPe/+gO+4dH5FLw6gvXKMucvCi4cO4MVy+cpyxiE+D5fEavKmNDzoQWubQmtY6RlVuq4UdjG/uJSaSKAsKZztCZxoUo2hcJUS72S9MaIWKdlUztTlQWJa06NKJpFijdQxfxXHE25es7hm7HzTrlkMbSF4qf/4Wv8MGHN5iMJ0igMYGnu/djB/TekJ6oeHD7Y373d3+TnZ1tCh0Ns/dQ9IY0ruXG977BYNBH5xWTw6cEEw2byjKcNalmWJLlVWxW7FOLn9RoEy+o+n2aZoF3MbIVqVTHE0GOLOvRtAtynS+d6eCh6g0QWlP1qtjIdnpAW3j0eAHBcbR7h/lkwVZ/lY2VTQ529xgfHSB1EcXtvaDIcwajErGIaaxe1ecndUl8RpZjwJqY/LRZw2ynxVpBsC3Ox1yY0DpGWVIh8wKZmnfaekGwbWTBybgIhFJI4ZDaIbOCYthDBIe3LV5qtCr57fcNF66OsKpAUUdYQwSk0OhMxoMXUnlArK3pSCfeeaRKUJGILCzTthFbTzUswcP+7i4Iz9mr19FFjrOW6eFRWpQCZ2zExEPANA0q01GFYz5H5xmgqWfTUwsUG9PwtT/8Nr/8Kz/HoydP2H/8hI2tVeqmZTDosbMzpW0bWlPE2jkRPVWfVC6W/0+4vjGG1ilktU6R5Yw2MtbOXuTl13+G+XzK4d4Od2/f4P69O9y7+zF/+DVBVfZZW9/gzNnznDt3kfWNTUajAWXVi00QU2+0LMuJbcVlLJD0nqauY1SXGhEuuZdp/khsVwUUZcl8MaNtDO+++z5IzaDfJ8tK9o80Vy567j8doKVmPpuws7vDoq5PNa/pMrhw5UWe3PmQB3fvL1VShitrXL5ynYtXrzGZ18wm00TpDwQZoVFPjEh1ppekh0jVlqyMRhw4y872YzKtWF1ZRUnF1avXIstOSlazAevDAcZZatNSN21sBxJAK01eZXhiXVOmdaxlC7FMwRqDkIKy6iGzjKKqOLN5ll5Vptx1lCsrCs1oMGC8mJHlOcol45IR86F5zPvgPUWvRwgRoupXFe3CUJw2+BXRwAsRozJvHTrXqCS0vba6wtVrz/HBe99HK01tU9GtUHgUdz++wfdvPcVmA15+7jIP7t0nl4LnLp1ldViRKYXAUfZyqiID53DOUVZVhPalxDgH1oMMKJnFHmHdoZuuI8tyuk7VsZlsRmssWkYloKgVqvDeYXwgJ0LKUQ5OsVgsyBKL2HuPVpqV1VVCCEvFk05h3ycovoMdTzuEEhzsPWW8GLM6GHLu3AWqPKqa7I6vxDMuMlU4PDrAqQGteYRtWqqyj8gqVi6txq7qwTM5PMT5/Yi4mCgF6EONdwFpPY2zKLWIsGGIdabWeXSW4Qg0bZT6i6olAWcgKwucD7T1AtNMGK2N2N/doexXeEeSLZsx2lhjenBIUZXUiwaV5ezdvxNz+v0CLzz91U1Gq+uM1jcpCkUUH/YIND6ssyECQjokecxr55/ew+/ZIjTvcaZBSEk9kcx2RxAEVVkTioqQ6ji0VAitCHhsvcCblk62OASHQBEi4I8JEus9bRNDXJ0VBBHI8oLpZMbYSQo3QroMlMQFifAa7RRKVzi7wKfq+FSTHtmTiZLtrENqloWvse9RLCiNC9DRW11FScF0fITKEl1cCJq6jjp/3sdNoGNebjEZI5RkMFpFBMF0fEjRq07dA6nXy/jaN/+A7af32H3yQ168fp3hqGKxiB6Jc/vUTU1pqkTfj3JR3kVPsrNmNnhaa7FkyCSsKhFMJjOUUPT7K/QHa6yuneeFV95hMj1gd/sxhwe7jPefMjkac//ex3z0wbsYa2KtU1FRVX1GwxErK6usrq3RHw4pq4rx0ZRvf+sbvP72F3nhxVcj+0jEJHDomvrFux4PaevY29sj05IPbnzMYtFQ9gSHR4cY41ksMr7yxTH1TFE3gnrRIHT20zi7IGBrfYNh7y3u3Pghg16PjbNXWF3f4Pz5C/RHK4zn9xmNRuzuPUiFoY5CZ1R5QaGzZYJfkMSVfaDMNOura+gsp2lb+v0evbKizLMYtYjYf9dbR57llFmGLYpIQnJ+Wb9jTNLKsw4pHE3bRuOT5xRVj2DjoasyTaZ1Ut2HEKKRksDayioLY6LhFYKaQNs2SC1i8XJR4NtYmN2vehRFydHRIVu9jL1TnrsRZIn1pT7lpGSixEfBYMnPfeVLfHjjA5yN5JDWxPyeDzAcDHnh3DrPv/kVPr73lO98/z0EnvW1VUYrQwaDHvjYM80Hj/FEyE1rjA8EGzuQx+7VGQEfBccBRKAoS7qyD2NsjLiUBqJ8ldSKAh21Tn0g13lqOimXqkDeWopM43w8RK21S4GGTi0jz7NjmasQ0RzbWrLs9FqOosgIymOsYdHUTCdHaJ2T9Sp0VtEbjPDG0TRzelXFO2+/RakEOw8fMjs6wFHhjI7CFlmGMzY1641Cy3lZUM8n5GUPU8/RWb7Meassp20iWcu0NSorwLd4L8iKjGbRkuUZxhiqfp/gHN44FosFzjqMcbi2IRcVgli3a11AWYsxLdWgYnK0oBgMQUje/NzP8eJrb5IXFc4GWuEQGDxRjF2IQFH0kDpPguySn9R78pkhxy7vFIIAWUU9Rp3jnUtUfY9rGzApvwOY+QJb1xTDISLLUMojhE7kENBZTqZByzbKEwWPNw7b1hRVjpKgpU1yOZIgPUpkqI5VGTwuVu8CYF2bIjURVRyyDGdMWow6id9GHT8lBbUzeBch0/lk+v9r773D9LzqO+/POXd9+jxTNKMuS7LcLeNewBgTEghgWCC0DcmmbJLNpm5Jsrk2+27IJiFvdt9lN9mQzYaEECAbqiE0Y3ADg3uTZVtWsXqZ/vS7nvP+ce5nZGHL1owkjzS+P9c1F1gzz8yZe+7n/p3zK98vUWjUQoRlEQVdhGVh2w5hp0OaJHiFAralCFuTlIeWUfA9ZsbHF9xeblsW551T4bGtWxgb9BFSkcQJQRBTKRewLDOsG5djgjCgXCrOXac0MbWMVCmiJEVLH2EViMLI7DKFNG8uLUjiGIT5eULDQG2YwfooApVJW5kBzLDTpDEzxeTEOFOT40xOTLBv3w62bQswOovSpNWkZKY5xdqN5xLFIVIaJ+c5TTYh5rYYcRQyMTGOYwnGD48ThOGcSWiammYMrzLMivWX0es+yKNbY6SUrFm92tQ5FohjWZAq1q1ew4qxlTQaTaampki1SX8eOXSIVqNJr9Mm7nVJ0ypKS5xUMVCuUPR905qeOSVrpebawAueh+95Wat2pmqCQkkLR2QqJFZ/QBxM+UZjOaahw2QREvouFUliXAnS1DTTSGl8B5lrrEqNZrQ2MmPCMvdsueCxrFahEwQo1zZKE2mE1ha9KCYIuni+j9WJKfkFqqUyca9DXTewTmK3YNs2KlVGai07QVmW0T4sOj5rV6+gVKowMz2ODmOiOAaMbJRng6NDpFZ86Rt3GkFhx9SfKuUq5WIJKSSD9ZqxPbJsPPeoGae2LNN1OKdgI+b+DsbPy2gZdrodbGnjeu5cd7ZKUySCJE2zBjcxVy5Is6CllGnAchzPdINaci6omc5iM7dmpKYs0xgmJb5tox33pNLktusyuGwM2/OJVYIWFrbj4RU8wGSegl6AcIx01caNF7BibCVJGNFsNPn2Hd9manycYKZhxCa0wrI8ol6IUygQRwGO55MkCmEbVROVpU3TNMLxfeLYZKKMD5yL1jFRaOQNtZQIZREGYRb8bZIwRUrHlCakQxhEpn4dmrnlXtv44XVbXZPSjyMQBUq1QUYHh3Fcz6jAZJq4UvRT4Vb2/vPMM9vut8Ad59rN92JLrTG2K6ZTLA66hK1ZCgNDppVYZTJWUoA0aZRYguVYRj1Za9JYAZFR9LDNa4QwitdKWKg4Jo1DVJri12pg26bz0coeDZZldmD9TqQk8/DSmeyTTs1DPk6yo3/mg5UkJDI2wSmMTFdjJpIc9NrESWqcioUw5ppa4TguSRTR6/aQjoVXKtGXyxGWR2e2SdBqmM7fk0gzLBsuc8kFa2k1Wriuh9YQRTFJ7FMoGMHUOErMAHexAJgBzyQRSGlU4oVVQAsHlcRIy2i5aS1IYtOFJaXAdd253WzcM12crmsbzUrLAxdK5RrDy9dynmUj0HQ7LSaO7OfwoX0c2LeHQ4cOmxqUFNi+qU2GUYRjy0xH08LzjHakpkgcJzRnmti2xeThw0xOGIdqy7LxPJ+RZSOMZU7Rmy68gaLb5vDUTgaGz6FQKM+dShaCytrzp2cb6NRYHg0MDKDRtHs9M4slJYNDIzy5+1narQa+51Ms+CwbGsZxHRxpm4Ym1U/tmiKJJcXRkZHM3iVVIFKjRielaUnXWpssrTKdnnbmJm40Nx00giiOMT1RAsdyUUJjCUnfhBwgScwuWimNLY3fndIJynFJ0pTpZgNpSXrdHlZlWdaJGuMKI3WVpimtZoNisYjneqwSMQ+exLWdSycrNZf2R0CiEg5OtrnvsWdIscwJAGPOOT09BUmXwurljJ37Gr71/S088dRTDA1UWDE2wrKhOgXPRQCDQ0NYlsBxHSzbzHlamc4qmMAvHAtLZkrzFsRxjLQcM5IhBKVyGZWk2ca3b3RrdvmWZYQWLJkZ10qzQRBSmrEg1zF/0zTJ/FlEVqNSJImir4cvrSygZSMQqU6yssbCKPk+l65ZT6IV2w7tR/o+rutjuebZ1G9UU4nGtW0sx2OgWidOErY/dw8z09OknSZp1MMv1wnaWWnLzjQaBwbQaYpINUrH2aEi86HUNliOGXPqBUZAQhkxB9vOattukSQJzYEE40ZveyaY6cTMNtqOCVBBp4flu0bIQkIcBLilElG3g1cs8szTWzlvwyYGHAeQmSSZNAcejCGu6xURlkKoTPfxVNXQzBxajEiy7p44QakEu+CDTlFRiO35WL6HsK259nG/XOmXo4wQqDS1lzSO0KnGssyRUgthPmeDVDaOZzoYhW0hLGtuXsToHqZMHtpvCsECfL+I53l0mm3SNKZUqaBUShIlpCrB9Xzi2FiyK61xPM8oNPR6RvnfcrC1JgpDHNeh4tfpdTokYQ/b8/BLJYJ2G5XEVIZG8FyfXtAjjUK8Ypn2xORJmXxKabNitEqrSKZXZ2wwur2QSrlAq9UkjkxaNkn6O+GUMNRIRyLsEkkqEKRobdqohZRz7ec6ezhGYWx+f9vCL7jZn9WoeIRBB9u2jSICmhgzs+f4JUZXrWPdxk2gUnq9NkkSMT0xSavVQkuPOAozwVrTbecVCqxcu55adZAnHvoBaRLSabU5cPAgcZwQJwmO41IuV1k2toK1qzbQ2/0Y437IoSMJF54fM9N+nlnhAhFCMjRUJ0wVloCwF2I5Fu1WKxO11QxUKkhpsWz1enZtfRSVTlEqF1kzthzPdRC2hYVEWmYzZ2bvTDOE65rApJSaG+A3nnL90nXm04U2WqVzEmKZwn9W97GESdcnWfCTCFKtjeVNJj4rJQhtHvDSktgSVGJmL5MoYe+e/aRaU6wNsX7VAN2gh6sL1Ot10jAGzzT3HD5yGF9qVtdP7tpqpYwMnjDv526seHL7Hh57aie+Y7FhzTKuvuJS7rjjDoSAbq9HXCkwsGwZV934Zg5O9fj8l76Gb0tsUkQaYkkzO1cuFamUS+YELM1wvWVZJvBnQdhxHGzbKPUncWb0abvmb5TEZl1aZ5mcLGApU1fTWS1ap6ZWZuyLTD3Ntu25Tsl+rbC/idHanBCF65HEMbEyIsxRnNLO7IaGhwZPahMmhcDSimf27iGyBTXPCBKL1GSNbMtGOIJIRaRCUC1X0Knm4KFDPP3k0+g0BsejUPXRqaRUHcCylBGA1hYqikxA0wqljMoTfUslABJzUEgVSkVYlsXAwDCNRhNUStQLUCmZ2DeZRmxyVIYvk+NCK5yCZzZgrocWCstJkVITRSm9RhMVR+zZu5vh11yO5ZhUtbAsk5lAYzlGSBsBpApJ+pIzfvPcRigsYpQ2Mj626yCyOQdhCWzXw/I8pGNmQrQwMz5apebYXPCRmTJ2koRGRcSSZtpeg+V56Liv6m52P8Ky0ElCHEVIxzHDm7ZNEie0mrNIy8ayLLqtJkkU0ms0gEzaSkoKlQp+qUKSpIS9LsVCEUtKktA0h7gDAwSdLt12i0KxSMUvkiQRYdDFcW08v0bY6xKETXOa8Qv0ZmaY7XXQaFy/iApCOo3phQ9TarN7l5ZFrTYw92BUGrrdkPqgiyImCCNsNyYKY1xXkaqIKHEolsr0ejEqVdhOv9nFDEGqbFLfspwsHZMlAS3L6NVlqgnSEvheAaQg7IVIKUh1SqFQNJ1xTjEr6mtK1TK2rfG9KkncI0oUs82ukTZDmgeCX2V0bBW7n91GuzlLFHbZt3cPSWL840xXmoe0bJJYMzExweSRIzywZRvFcpXzLh6gXjlEK9g4NzO00IubxhEDlQqFQgGdQi8IsDL/i0a7S6dttPJWr17L8NAwzWaTUsFjcKBkTl+6b3GUjZVIgdDS2JYo4wyhsxQXWmJnAgL95oS+7JbMUr1CKZQ0zSBSG8X4VCtsaRpnyEYiLGECMmQiBpZt0u1S4HsOni3pBYIg7DFQG2BoxTpKlSpuoYDrFanUBoiCkDDsEQYhtuPgup7pANQBdSd9YVfqCWMCdpimPLfvCM/s3MfhiVnKZZ+brr6Q9avHEEJy38MpYRzj2ZJKtcp1r7uJq6+5Dun4fOYvP4YipexZVMsehaKHX/B57rld1KoVCoVV5jmQjfJEcUySpRwdx0ZLQZSmJqgClm0TK4XjZDJVWWoqTRNs20WpxHSTYs+lFftfZ2epOddxQFtolWSt+ObvJ4XRf+zXyQQQBN1sJs3MrlnVMsWif9Jt+1prHt25A+V41AaGsuCo58yQtTQjJRJFoVBGaYWKIw4e3MvsxEHCVg/SxNxr/RlfFGizVi3tzFHbyNSlSYhSR2fnzCNCGUeRbKavUq3Q7fXQugBCYDuZ9Y5Is7lV46hiWR5IG0sKcGwcmc0kC50F0ASloYgp9wgp2b59G9dcdT2FomfkDC0JOAg7xZZkTT39rvOXfhbMr8tRa+xiGeW46MwhVmSdbZbtIF1z7EzCMNuVgkpiI2vlOKRJhBDGCkBIo4iv0hSV9FAqxROmwJwkUfagsBCelxVzI9I4mpshsyyj6JyomCQMIU2Jwh5R0KOvYWh2wQlBr2t0HAV0mrPmwZLlvkU2g2JJ080Y9AKjKZm53fY6HcKeOaUVi2W6zSZxFCAdh3KlSmd2lqDbQthywW37ZjATE1zmis6A0ERhik4Fvl+gG4a4pSq9OEYQkyQJUSSo2gVq9SJpktLr9ubqWb7jmJs9VZlrtMhuPGtOd86oKZA1KMSUKxUc2yaKwuwUGsylWD3Po1guESUp3SDBLVSxPZ+Zg4doN3tGV1NIpG0xODzC7OQ0UxNHCHshO3bsptXqGC8wbQY+/YJpXGm3GtgSwkSTigID1WX04mGGnD1E6clZcdi2w2yzQ6vVoV6t4vge7VaXVCtc22V4cJAkUQRRQBCEgMR1C/iuGZh2XRfbcYwjciZrZBTbjftcnNVuLcu8P4zpaWruLTC1S51kD8ZsfjFzFDBv6KP+VcYJvN8+ZVLJUpt0GtKYitpC41qSSrmAyhqEEiUJFaxcvY4oG+GwHJuBgTrT01P0eh20NrYmtuMyODjIBr9HxWu+RPLmpVFKcd/j23l4607SNOW8dct5/1tvoFL2CaOUp3cd5J4fPMaO53ZywYWX8Kabb+Tiiy7CksaW5La7vs/O3XvwLFMv0TqlWiojRUqtVubRRx9j44ZzkZ5Hmips25QZrDhTis/eLxqJ47mm7p1mAsNzgsNqTnQ4DAMKBTOUjciUjLCPmXEUIqvRWXpO4QZl/u5hFNKcnSIKAwrFIrVanUq5jLRtLDurUScmG+RY1kltwrphAK5NdaCKFCqzcNJobTopdRKZoOK5iCwbmlg2F118Kd7POmx/ahtBu00cxkRxZBpokhidpsQqNZk1rdCJGbsxsnTZCUubTl6VZIa8yjgQtDstCsUCvu/R12btD5+b/zZ/kzSJUCogzkpAXd0PRaa+nG3VQGqkJShX6ixbsQwlTBejyOxreF5tEoTxB0WZktepSjlatkW5LGgFKUI6SNsxPmaWkeGJe12z7NTYnJDVHBCCNEnQIvMpszPViTRGJBqZ1a2ioIdGmPmIbEjbiOsauxmT1+2ikpYpYjrmhlRCm9b6LPUzl8/XmjgMTNeZNI0dps5ndsRxGholiay2R3bxNKBik5qzLHPSSwJFo9sx/ku2g+O6BN0O5jQo8Qr+gk9oIpuXE9mH1lnruLAJ3AqtXkh9bCUzaY1ExgSxwhWg4oRuq81zzVkKxQpDo8solYqUpSYME4KwAwh8r4hlSeIkzZybxdzOs984YjvOXJdYq92mVCrQ6/ZwPVPPcx0XaZmdbBiEmWSZxC0OUK0nCNlkcuIwSamKFuZ0eOTgXiYnDvPY448yMTlhus0ShWWbJotyqYjjOqRpZFQFLIuCX2GwPoBtlWlFAxQLEwu6pn201kZnrt2m2WpDp5OZcVukSUIUR5TKJZLEItDaKNY7DkGc0A1DqqWicVaXCiXJfBFNg4gUYClNKo2rgdYCK1PDUamGvtK/MNYnZG/yJEnnzG37Oos6VXMPYikFKVmg0xJ0auyaAN+1KBdcBqs+SayZbAYUC5Kde/cz0wpxHQ/LMTU9AJ2YYOoVfCwhqZTLBN0OfjqNshLT3LUAJmdb7Ni9nzddfzGrlg3juRazzTZ33beVJ7btYbbZ4oL1y3nvO36BtatX4vsFOt0OSdDjSGOSL335m0TdFvWhKgXfoVIuobTCscCRNk8eOsDuPbt4zeZLzQlZmmeI6arMmrotCzdTjfD9grmutpkVFGiEJbNBZ7L2/UzFIzvt2I6LcaTInCAyE5Fu17gXAKazNKsN1oeGs2dd35YpRiiT8sWSeJZ/7MN+ofcsZv5KJTGQouea30zGy+rbrqQqMzwx2YJapcpll17BxRdeik7N74NSZgOWZuLcz7N7EspIvBmj28z+Kms6QjNnDZVqATrptyyAVihU1uav5jZqJkNhrKm01qTatN/rOWd0jRZZl3smpO5IB69YoFQ2OpzmWj8/aCkUcs6g92Xi2fwCmkpTmkfGUe4g2EZ6yfU8MzGvlekciiNUEpsCuBBzD/n+hVQIrNRcSGMpbtJtaZKlaGTmupxpO6ZJQpopZdDXScuK0SqOstpc9nO0eeJoYR4QSmtsoSFNzU4kVdjCKPGnaZz9EbNOPJ3OFXXNVB+gU+IwMjYzkP3xzc3Qa5lZOtPQIknC0ATxBSC0hiRBZydcpRUogfLLKH+IdnCQZfUCaVSiK1Jc3aWQddzZUtGanubxB76NSh02nHcZGy64iNpgnVLRCBv3goheEGFL25R4MreDvq+ZlXVx+r5F0O1Q8H2T97Zsosh0h4ZhSG2gRrvZplQ0D5/pqUnAFMWHRoZZtWKAH3z3ftxCBddyeOyRB9nz3LMcOHgQpRLS1DThOI6buRV7ICyEltSqdTyvSC9oUS0V0JZNko5S9J7pZ44WhFIprVYLhCDSGpLMP0pHtHoB3aDHQLUK0p5rAzeiviH3PfE4N11xJUN1d27gWguz3zRvbo3AqE/ECcbFWGmkkiiZWfjQtxPJWvmlILFNE9NcBSs72VmWCURaCKxM2NW2nayzz5jTetkpbrqdoJRRIZmYnmTvxDRueYgkTUhUgtPt0rRnSTKvQUSmz9luodOYAa+HsDzTALAAhgYqvP8tr0ULmG10uPuB7Ty+7Tks2+HKSzZx9WUXMjw4YLIhaOI4RKUxSMnn/unbTM1MM1DyqdeKFIoFapUClZKL77iUShWuvfYGVq9Zk50ctBFuyBoifL+AlJI4iU1npTT1FrM5SudmX/sNHEKYlLvpyDvWpZnMdcPNNmhpqnBcl0q24Usy9+n+prrTMdkk1zV1Zq1TZJpCetSBQggjjrxQhMC8VxIzAiMyYQeNZVKF2Sbf6JFLNGaTmrWtIKUZvNcSE3B1grAUpGaMXug0a3JRaGU6Mk1gymrWKktRYoKrCSBZUMr0GXV22uqfmPpxRmvjp6a1lV3rzDeRbGOGRsksoOrM+9IiC9LGLJi5+dpMAtgcMeacPZ6nXvsC5t0U0umkELURVoDluKSZO6u0nOe1z9pgkwmGusYEVJmpfBPs+/MimcyV1qgoMtYyWQ0o7nZN8bL/C2Vfa45fHC1iiqw4rTITR7IzVvYm1ro/OKmPNqJAVqPr90MbC3MhFI6tSBNh3AFSnclmmeHR7C88VzAVSpMoDWk0t4aFoIQwXlfKMrUYU4BEO2XSJKHRTXEbIUlREceatlWiqjqmC9O2qA8Ns3LNSp585FHuvG07d3/nm2zYeDGbr76W1evXUioXqUiLKIrodQOCoIeb6eE5jlEaR0Cv18X1XIqlgklBRhE6jNFaUSyXCKOIMAgJeyGe7yGzoWgpJXt2bse1FYeOTFKuRLRaTSq1In6xgBYYU1Rh47gWXtHHslz2HzhEqVplaHCIRqNJHE8BmnKxQLmsKNdW4BemsBeufAVAlCSkSWLat32fTrttVCEcGxlbtHs94jTBdzwcr0AYBag4oBkq7vnB97l882VUK1XKpaKRt7IFTiZxlCqNQOFn11EpZQwPtc4CnKlTCSFMR69Wpl08O4GhIe47LYt++7jAduzMDSjrJMx2/lJKoigiChO6vYAj4xNsffZZCkPLsR2HoJcSxglBHJPMzBgnCtuIaAsEs+02g0WLkYqFSgLkAqWvpBQ8/uxeHnvyWQ5ONhgZHuA9b73ZqHwUfOOsEAboMMxOQZCEEfc/8hRPPL4Vz3WQwpjN2pZEpWZ21LZcCn6RtetWUq8OmCY0IbAsieU4mSmpJo5CUq3wPWPqKzCpTKX6dUGRuVH0nT/MQ7FfYui31c+ZDms91yktZf91Escxp7wkMfWzSrWSnRJNI1WapoRRnJUw+uK9Cs/zFny/mv1tghaOkQSWCUijCqSVQmXPNa0E/ZyjEVrou0kIjBFnmj0fHbROzWZJaxC20cBUMnu26kyw2zw7BSZQZmaIWeo880AU5uuFkigESmR+hdoCUrSwTTAU/VyXyDQ1BSiBlqZjEpE1EyGRMlNiUtZc0JOZ6agWGimytGiqMq3O41+7+Z3QlCDRFsQJxGZQDmHah00HIoA8+vAXEi2CuRSgtMzsmbBspO2jMekuc8I1OV0RB2QlA2SikK5vdsRpnBloquy4nan2ZxcMR0KC0duzhKkNWRYJEHW7pkElUZBZXhyTmhQwNCBYPZhS9SFSARNN2DchCTqmiQUh6KvLa20eDubUZ95ASqVzXT7zRdmW8XpSCiGU0ciTEmWbTqtQ+DR6Cu2aG68dwFQqGBQgpMbGY826TfQ6bbZt3cbU5BQPPnAHWx+9j/qyVVx69fVcevll1Idr+IM+RpE8MqmVMMIv+GYQVwoKxQJJqlEp2LZLsVwliWOiMKTbMw7OYRASxwm2YzMzM02aJDy3/Vka7R71kUFcq8Bso8GOHdtpt0POveBy9u/dSXN2Fts2J5lms0WxUqVUrBBHxjx1cHiY6ckpHnt0C6Mjw1i793LdDZdgyYXbxwghKLgu2nGIkoioFeEVCug4Rlvguj4F38PzPYQWlMslnnriIRrTR7AFTLbaPLb1Sc5Zt456tU6p4OO5Dp7v4Tg2rmPa7h3bMY1SlkOKytr1szrlnGq0cTkn0z8kVSRK4/Ud2zNFC/NeU0RpgkoVcaKMjU/mJxcnKXGS0Gy1eOSJJ0gLFZY5PmEU4WVzceVyFfr1bCFwMoX9QrnEmjLUKqC7Rlx6IUxMNfjSt37A5Ret551vfh1D9ZrZZWtFFPQyn8AYKUy3pkoTtu08yB1334vjSKpWgXJBUvAcHKkpFV1KlTKFUplOEFGuDrDr4FN0g2mkNidbrU2qNkqN1F29PkatPGTSrJbLyNDyuXGivn2VlHZ2H5jv4TgOSJHN+pmTjtZ9/dG+Ma75fL/WqbXKmkay2r3OzIEzQXT0UcFi0FhCnJT+KFqZ9ndpkSCN7ZUQKJWYk5TITmD9k4zqB6F+WlAbFR9NdvLScz0N5i7sd+D2N0vZ65CgHEChZRYU52ZJzQlLY5y05zZk/SUL0Nr8zsbEmSw1KY+agAgAywQzLPrfWfevfXYSNBmLbBRDmr+PkdkzXfWn7ISmVDrZnZ7aM5/XnC0cAJ44+W+zdiEv6neyKa0Ryrg9S7tAL46NWkF9Gd0gwI4itHTQScg0HrZqU3LMw8ItlFizbqOxjU+fIZxooFWP6cO7+Prnn+W2L1c57+LNXHvja9l47kb8okeh5KFSCMOINDGNKVNTM3h+gTgKqdXKxm8rSeh0eriOSxjG+JkIscQMae94+hn27j/A8rXnEdireXKywGRQoTXwOoKS5pCCS6/q0t07SdAbJ5rdTqU2Qcm3TLu6hE6nyezsDFqYGuzOXbsYHhvjoQefJgx7C/6DaG3mnzzXxnddiqUyjuvSnJ0lCXoUC55JR3Z6OK5HFPaYnR43DtOWR7lUYmZmlvH7H2DjORtYuXIlXsHH7djGckZaCGljSXAsM/gvEGgpkZjdvkCTpBrbskjSdM6eLEky5QxlGkk4KpOJRhsFkUx7T811zmm6vQ6TE5Ns37sPb3AZY8tWAIo0THBwKRWK2MrUrKM0xvFMEE4iI/QcygITtsOQHZPEC9ss+J7Lr/2LtzE2OIBC0Om0zfCy6ho1HmVm/uLE+ObtfG4/t93+XSwpKBULSJ1S9G0KhSKVko/QCQVboJKIffsOM7bqHJ7c+SBh8zC1ah3HdeklPTQpYRwQJQprjxk895wCUaq44uIbuejcq03NMksRC8y1VYnxMovjKJsBNH+/fuu+mssCkUm4HS2V9IOcEMKkH7MGCJFt5qUlCIIenueTZOMFSbzwER6tNe3mLEE8heP7xh/MLmC5IKWDtByEcJFYz0sM6uwUZWWBzryfRZZvPlrSE6Zso625pLdCoIVlUpvSpDaNEZzM1nP09KUxKkv9bBy6bxmmj57I+j9JGNueVGD6KUS/NUSak2WWUJz7vbN6GyLryCRBKwstTHlI6WSuWeV4zLfLcWQ+X59z4igtso4qUy9I7aKRfrIkQhklFBWFIBN0muKXS0w1FL5WKB2B8in4ZVauXE8YaeJ0J1GriScFtpCEcYMtD9zB/ffexdjKtdx4881ccc1V1IeGKJXLmYJKTLvTMV2hCGZnGtSqAyRRknV6GdmbXq9HoVik1+3SmGlw+Mg4cmgzD3WvYnxmmDAxOy5lKeqliBXlAMezWLuuwraJC+nUbiJJpiF6jEG244mEVCuENLYxCk0QRHTaHRQWYXgSunjCdFSWikWKpRJDQ0M0Gi0GB2pEaYXG7Aw6TsyAtaXZ8fijNJrNTPbL1EE0itB2eOjJLTy+9UlGhodZMTrK8rExSpUynudntRxpivR9vc3sodgP/LZtk/Tb/JXOhH3NqU1lGoBAVlAHtEYKI37daDRptJpMzzbYPzFBaWQF52y+BtvxcKQk6HVwrIg4ibMsghH7jhUUPR/HK+D7BfMw8Ms82Elx0wKBXNg2rlouMFyvE2VZhUq5ghD6qJKGNuk4jeDZHfu4/Y67ieMQ3y9QKRVRKMoFh3LRxZVQLLjYtk25NoB1eIqHHrqf8rBNz7WZ6s5C1wwu+14BlVhYWrJ8cJRKqcx4a5LJxgG+++Q32HV4OysGVzNQG2K0vopSoYrveSRZZsUvVtBaE0ZGvd0YDluZX1o/c2M6UZPEjByZzkdzenZs15wQ9NHZw1Sl+EXjQt4PhmEcL/ienZ2d4W/+9uMkUYBbdLHtMo4rcR0Xy/WwXBvHLuLbHrYrsGwP13KNPJYtELaLLc08qOPYWNJobM51dVsCiTTzdGT3qZCZR56xjurfvzJrmzexyljEICwE/f8vzNylFiBMGUcjM+MCDVk9TWWlHURsMmrZdUZgUqeYE2fmJ4/QKSkaKYyvmkojVBoQZxJux2Ph4+w5pxaTwEYpAYUq0i2iwybIAkkYkgZdLHxiZdIbYRgTRym9tGeGxBNTHygUiixfsYZeGHLkuT24ac+cNmzwbSgmKa2J5/iHv/3ffOULn+Oqa67j+htfx9oNGyiUigzV61AfMKc2pWg128aa3rJBpCRxTKVSpd1ugbDothsckefzbHodQVIwuyyhUKnAJuVdl7dZX2sSxgFporg+sNgxUeLbTw1x0LmJtl7PBudRinqaIIpMWs0FSzbZtWM7w8uXk/WRLeyyKk21UkYrCIOA6clJHNdFOJL68BCdboc4DVAaDuzdTbc5S7FYIAgj0qyLTCJwCj6eVyCKQsZbTfZPTCKe2EKp6DM8OEjJ86nVBygXTODwi4W5gV0JxJaFldV3tDIdZklq0idxkpCkZucZR1Gmst9jpjFLu9VmujFLN06wvCL1sRWs2HgRo8tXUiqWKJZKhFFoTnSJotGcJYp7RKlN0fEZGRymUCoapQ2VkqqUar1Gc3aWZijoLdA8VWRjCDpr7lLC1D6i2Ege2bbNTKPND+5/jOd278R1PKqVEqViiShKaHXa9IIQ24JCtYjteriuS9ALGRwc5MD4EZJWg3a3Sd8mxrFcWuEEjusxWl+LWxpBuAVi0URIh4pfw7UFR2b3cmBmF/sO7WTt6CbWrthAoVjGcf1Mod8o4/SdIxqNphF6dv3MUFaR9ptRskNEFIVZc46Rh+rXRIMofd7MoXkwm2arhXc5Br2AiX37CcMAt1TA8YvYnsa2fYRVwrJTIzsoNdgSoaW517RCaseMIMmscCNMck/orLNc90tE5kQltchKQ4AAqa2s3phJrgmJEEb/UgjzfSzLlHksobM0a5aaFOZnIOXcOIrV/14SExDRmZkqgJrTmIxVDEogdUqqI8BcV51ItIpI0giVhoRJwmxz5rjXLg9oZwxZ55zjkRaGUVGK43hYrke720IHASXHTN0LyzE2N1FEV7WoZmKhtm26hkqlEqNjK+jMziBnAlxLEglQFvgpVD0YKHl0wjZ33f5P3H3Xt7jowgu49obXcf6lr2F4dDmeX0RKKBXLhGFIs9UwUkpRQmgFCCmZPDxBVL2Y58QYoTYDyKh+sV3ikrCsFOL5Dq5ng04p+iGO6HDn44KQGjN6DbsYZJN7H2l7G2G3w8zMLN2gR7k6wNT4ybXtK62IghAhLbq9Lt1ej1qlRrlUQqUzJGFEGPRIwpD27AydbpvVK9ew/9BhXL/E4LKVrFi+Ast2CHpdJiaO0JyZwfM8HNc0KQTdHt0oYveOvcRhBxXHuNJGSHCEMA9j2yZW6dyQbJokpErPCROrzPLFFI8dvLKZ8fMKFWr1MQYkuK5nOkyVpt1o0mq2KLge5UqRcqmMENDptSEVdHsdVGTmlfxykYLvMT09RZIkjB85Qq/Xw7KcTHdzAXerJjuVZu7fidHetG2LIAjZ+vQutjy5nXanZYKW7zFQq1DMPN+KRYckiYxdTtk3os6YLsLzL7yEtgi476m7SJKI0YEBHNvBsSLqlTFWjqwz6h2JYPv40zSDKdYuW4dvl1hZX41SkuVjaxio1EELytUanldA65S035YOmdSVplatmLqYtMwJm/5s1tH/7TeOpEmEQOBl+qJeoe8PqOc+zCzcwltzo17AjseeJon7AuEuti1Mgx1Zu4LtIC3jX2jZNtKxcSwzQiUdI4ItbRcpHGxHGRcU7WQSdykiG162szqhkBIlbKRUSPpBzclOa5juQ6SZFZMRGqffr4REofr/Icz5TAid9UIIk3LU2ZiKUQJGiqxjXKYI5Fy5RRKTaIXQKhNeTyBJiVVIGodEqSKKo+NeuzygnQGY7JIRbE7dGkmqCNsN/HIVHQcEnRZpL6ZQKpuAoVLiKCAOY2JhOvg0Yeb7ZppKSqUateFRZhuTSBSOpdCyb3cProKS6zJU8mn1Yp7esoUnt2xh9epVXLp5MxdcciXrzruQWn0A3y9QKJbQOqHb7RlriEaIX6nyxS1DdJKjzQxzuzU0SSoIIjMjFEUK2wKdKGZn20RhgvYUAsl0WOHh2U1Uxu+HcBrLtlk2OmYsK/r1pQWilCbo9YhS49NXcD0U5iQTRD5xkpAKSaRSCvURZpsNdu3bz/LV5zA8tpo46NFuzmBZRvXdtmxq9TqO7SClhe3YuGMOrlcw3ZRxSBynDI4sQ0UhzzzyA7q9tnGEwAzL2tJhfGoSlGKgVMT3CjS7LeIwQgtNtTbEyjUb8csVLNsxotOpJo1DEzzSlIF63Xy9Sul2ellKOqZSqhDHEY5jVDcKxeJRsQBpgWXc0S3LNsLLC9UfzWaVwGSSWr0mh8YP8cy2XRzeN0MYxkghqVbMadV3PQYHa9iWxK74CDmERlEul/BcmZllSuxuj263SzeZwStYrC6vpOR6xqpGWpQKBSYbh7EsgWf7RFEHz/GolQfp9TrsObKTyeY0Dz77Pa6+5HVs3nQtjmNSjpZlY1syS4WSjfqYU4LSzM2O2bbRvXQcc4rzXH9u1qofqOZknoSYU+F3HHMKbjZbFIulBd+zSZIQdgMQAtuzsAREQWJMOrUmTU2gMy4D/T+Cpj+EDCYzIYWFU/KR0iLqtI/pFO/X7UW/1bY/xYARX5irkcmsaz1r4EP2U43mVCelNLJcQoAwM39kXaXmQ87VJrM5lmy5/a7S/kBAmqVxdTbilWa1wMjMdKaZY7jShJ3j20nlAe2MwMyeaWEhvFrmyGtMNhFGg7CbxnOnsCjoYNsWURAQOakZRdCQeo65SbKTQLVWZ9ZxkVHX1ATS2OhQCInnWKTCxtJQ9m1Gaj7tIGbX3v3sfG4f99xzN+vPOYdzN13EhZddzTmbNuEXCpTLVQqFMt3WJG1rI4eaZlf7vPcV/RmVFOglKdKWFG0jmowUtHoJWO7Rziuhib1VqPr11IIfYEnBxvNrjAxK9u0LeOLRhQc0gGani+s6FIslgl4PFYSkaUK72TTi07Fxdh5bNkapXMG1HZaNjNHstGm1mgQJrB4dMhY+hQJhEBEEHXQ2HxYGIUGny+iq1QS9gILvUhkY5Mje51AkeK6beQAqCtVhqvVREsuj3ZwmQdHqtKmUS+hShW6rTafVYNezTzAyuoax1etYs3oNluMwOzVNHIZ0ux2iXohf9KnV6owfPkhjtkGhUGTZ2HI6rTazs5O0220qxTJOwaNQrmbiBQGkCc1uzzh5L/iO1QRxjz37d7Dr0DPs2ztFZwKk8qhWa9TrdYJOg2rJoVhyqVVr2K5NEIZmnz7XLQjDg0O0Ol3CsItl2bS7bSZbB4kImAqnCFWRWqHKTLvNRHMKx3IJVY+Uo/OvzfYEQkMnCUl0at5PWwJ0krJ+zSUMDozg+yVsJ2t0UJowjUBnxq1ZzUxkM6qmFqaNZJywjOh0NjbRV4zpf/QxQdAhTRWNxuxJ3LEmNLm2jW0bI2STyhfZCIjEywxQRdZar/sah8qkR1vNFn6xwM3veCfDy1bzyY/+MVopSsVSFnyg7zsGZiwkSYzpsedZ9LuTVKpQiXHGULYNKkEnaeY1KTMRbuN3qLO1o4xCVJKkOJ5rfo7WIDV9TVOddTMK+g1xpnnI7Ckyk+hsQFsrUKmZ+VMqEy04DuJkcr05pwYhxASwJLtHTxFrF9qQlF/bl2VB1za/ridEfm1PD8e9rnlAy8nJyclZEiy8fSwnJycnJ+cMIg9oOTk5OTlLgjyg5eTk5OQsCfKAlpOTk5OzJMgDWk5OTk7OkiAPaDk5OTk5S4I8oOXk5OTkLAnygJaTk5OTsyTIA1pOTk5OzpIgD2g5OTk5OUuCPKDl5OTk5CwJ8oCWk5OTk7MkyANaTk5OTs6SIA9oOTk5OTlLgjyg5eTk5OQsCfKAlpOTk5OzJMgDWk5OTk7OkiAPaDk5OTk5S4I8oOXk5OTkLAnygJaTk5OTsyTIA1pOTk5OzpIgD2g5OTk5OUuCPKDl5OTk5CwJ8oCWk5OTk7MkyANaTk5OTs6SIA9oOTk5OTlLgjyg5eTk5OQsCfKAlpOTk5OzJMgDWk5OTk7OkiAPaDk5OTk5S4I8oOXk5OTkLAnygJaTk5OTsyTIA1pOTk5OzpLAXuwF5IAQQi/2Gs50tNZiIa87Fdd25egQ5ckZdKpO9ludMmTBo1mrcPDw5El/r4Vc2/yePSEmtdYj831Rfm1fnuPds3lAy8l5CaSU/P4vvJ9z/7+/QXd6i72cOQrveBO/vnv/KQloOaeNPYu9gFcbeUDLyXkJpBT4SYoO48VeyjHoQ+MsG64v9jJyTiOOY3Ptta+hUPTn9TqtNBMTUyRJOu+fGccJs7MN9PPOiGEY4Xnuy77W81xqtTKwoGTKCyiXi1RrFdDwxBNPc/gENm95QMvJOQtJD42z/vxrF3sZOaeR5cuX8YYP/CLfebI9r9d5jmRTxTomKJ0o1YJFwVH0X+w5ktdfVOYH27q0eslLv1hIJjuaND01GdNUwXgzZnTA4y2r7+JvP/6PL/uaPKDl5JyFpJMzrK7XEIIFPbhyznykFOyfDLn3qdlFW0OtaPOmq1fzqe8dYN9EsChrOGe0wE2VE+tfzANaTs5ZiGp3WeV7OI5DFJ1Z6dDTjRCCQsGnXq+yZs1yNm5cw8aNa3jyyR187nPfXOzl5SwieUDLyTkbiRPKvWDJBDQpBStWjDI6OgyAUordu/fTbvcYGKgwNjbM+vWr2LhxJatXD7BsmUulYlOt1tG6wKFDAQ8//PQi/xY5i828AlreTvryLLS9PCdnXmhNMU0plwt0Ot3FXs1JsWnTOn7u597G+vWabnc7WqfYdgnbfgvdrqJU6pGmE8RxAymPUKl4WNYgnY7P9u0NOp2DSCl44IHHF/tXyVlk8hNaTs5Zimx3sayz+y1cLPr8m3/zboLgC2zdugc4umcWwqJQGMR1r2DFiisZGjoPxykzOztJqzVFuSxYvXoFvR7s2DGBZVmL94vknBGc3e+GnJzTiBBgWRaebfH8B+0Zg21zRq5rHrzznW/E95/g8OHdL/ic1ilCCKrVVUxP7+DgwYeo1TYRhmX27evy5JN72bJlBzt27GF2toVSZ87ge87ikAe0nJwfYni4zu/80gcopgrbtljdCwkWMNNzWhECf/kIv/iBt9PsBfz957/J+PjUYq9qXjiOzY03nsuBA3913K/pdMZ55JG/plJZwcjIB/mTP7mTLVuepdlso/P2zpwfIg9oSxwpJZ7nUioVGB6uU6mUj/n89PTsMU0FURTR7R5tz9VaE4YRSmm01q+KXfAlF2/idc/sIvjanQAEZ5Dk1RxaE/63j3Oz4+BedgG9W97IX/z1Zxd7VfNi+fIR6vUOhw+/dA2wUlnB0ND7+b3f+wf27DnwCq0u52wkD2hLGN/3+Hf/4VdxBlbRVS5TXcl4M5mbW7ItwWVlyfPTVgMFgVBHA5xjCWzVJU1TbGJ67Rbt2WlazSZTk9NMT83QbneZnp6l1erQbM5vCPRM5NLzziH97kPoXrjYS3lJ1HQDgOCu+3nr//OrfGagwuxsa5FXdeJcdtn5dDrbXvJrBgc3Uancwn/+z3kwy3l58oC2hPE8h6C4mj/+8gwLPWQITEu1AFxH4NgDVIvDDJQcKqstRi922FiQVH1YPxDyJ7/3YcbHp0/lr/GKYlmSC8dGSA4cXuylnDA6jBi+71HeeNO1fOHW2xd7OSfMypXDNBr3H/fzo6ObSdOb+O3f/puz+p46GcQZ0DMdJZo4OQOzFC9CHtCWOFqz4GAG5uyWKnOCS0INoaLRSV5UNeDn3jhCoVBY+A87A6hWK6xXCtXqLPZS5kV4z0O857d/gW9867vHpIzPdI5XB1u16jqmpq7kIx/5BDMzjVd4VWcG3W6PenGxVwGdIKETnGE15OOQ+6Hl5DyPtWtWUD5wBNQpaDgQAlEpIetVrGVDOBvW4Gxci7NhDXKojqxXEb53SrbharbJ+i3beMPrrzn5db9CTE21KBSGXvRztl3iy1++91UbzMCIAqv0ZfQTc44hP6Hl5DyPyy7ZBFu3L/wbWBJrdBi5+VImRy8i3biJ2RlNr6NpdftzUhrd7TG03KUkuhQaRyhM7qPUOIg8sI/00Dg6mH/9Lvz63fz0b/8Cd93zAJ0zyOrmeOzbd4RKZTVHjjz2gs8pFeddjDnzJg9oOTkZQghes24l8TfuWdDr7TUrKPz8B9lpn8/tX2iw69ttVDLx0uLBAqSo4fh1hldexYVXF7hgfcAKtR/x6CME9zx4wsFNzTZZu20Xl22+gHu//8iCfodXkq1bt9Pt3ky5vJx2+9BiLydnCXDGBjTLsrBtizCMFnspOa8SisUC6x0b1WjO74WOTendb2bvxT/ObV8O2fnoAdLkBE8X2mQ3w67iwPYeB7b3+I4tGF61kouvu4DN//Imqt/6HOLZZ18oq29J7OXLSPYfbWCJ73mQH3/vW/j+Dx494084zWabP/3TL/AHf/B+du78K+L42LqlbefKHznz44ysoTmOzW/+8gf5H7//6wznJoY5rxBr1ixn6PAkzGeIWgjK//ydPLP5ffyfP57i2QcbJx7MjoNKNOO7e9zxD0f4s//t8Cn1QXo/8nZwnWO/UEq8qy495p+SPQe52vep12sntYZXiu3bd/PXf30fGze+GyGOBrBud5zNmzcu4spyzhjmUWI+owKaEALLsviJd/0om6cbDHa6J+SUmpNzKrhg0znIp3fO6zX2Oas4cs0tfOaPdhN0Tn0nWBJpdm7X/N99N5C++33gHBvUvEs2HRvo0pTy7v2sXLnslK/ldHHHHfdz110Ba9e+Ye7fZmef4+qrV1KplBZxZTmp0oTx4rbs18sOQffEBLjnnXLs+xANDdUJgpDZ2Sbdbm/eRejBwRrXXrOZwVoFKSWjQwOMVEqULIuRJGHnX/4Dw7/200xMHDt/Ui4XWb58GZ1Ol4mJaeI47wLKOTVcsmE1yee+ceIvcGzcW97MVz8xSa91etua9zzT46vLr+R9H4wIPvm5ufSjvXYl9rKhY9KOYt8hVq8cY8uWZ0/rmk4VSin+5m9uZeXKn2V0dJIjRx4jSQK0foIf/dEb+MIXvrXYS3zVEsZmTGcx8WzB7OyJdbvOK6AtWzbEJz7xJ4yODuP7LnGc0On0eOSRrfzmb/4hyQmmagoFnw//5s9QfuAJWk9uR2tN1GoTNdvMJopOucjqH7uRR6dmiOOEjRvX8mNvvI52p8frLzoX/7l9yMEBpstF7t26nSROaLW73Hn3A/R6Z88MTs6Zg5SSNaUi6dSJt4kX3/oGnqzewLaH9pzGlR3l8XsaXPl7b+Kcix4jetIEK1kt42xYc0xAU4cmWHnVJa/Imk4VYRjxp3/6aT7ykX9JrTZDo7GH/fvv5V3v+mXuuusBpqZmF3uJOWcB8wpovV7An//53wMwPd2YG+AMgoB0HtO7jmMzUPCJ4oRlr72Cw3fdz+o3Xs/00zupvu0N7A9C/uGRp7jjy7dTq1X4nX/1AdIvfIuo1eHIV+8knG2CgIFN53DL9Zcz+exuaueuY9UH3sZf/c3n5/Mr5eQAJt1tJwk6PgGzTAH+9Zez5+r38vmP7Eelr0zzhUo137m1yS9/4F1E//FPAAjiGLlxLdz9wNGvC0Ks+RQezhAajRYf/eiX+P3fv4lG4++I4y5R9BA33nglX/rStxd7eTlnAfMKaK1Wh69//e55/xAhBKOjQ9j20R/3V1/5Dhecvx6U4h2//Ys8ceAwex2bL3/sMxw8OI7WGs9z+Z1f+Uniz36DIw88cWyXl4bZZ3eTBiHdw5MAWK+58GXXYVlGrFcIQbHo47ouaZpy5MjUkhPeTRJF0dFIcWrmhI+HJQWbz6lwwZjgqwuYnzqbkNUyxQ++gwMX/Aif+eNDdJuvbDpm95YWj712lE1DA6hGi9nZJl7p7FZneT779h0iDAeQ0kaphImJJ7n66vdy663fOeO7NnMWn1ekbf+iizbyx//6Q7S2Pov+obSkcGyCvQdZlaZUx0ZY+c9vIUlSWnFMkKas2X+YZ+9/cSfaNW+6gc3/4Rfp7NyLPTzIHZ+8lR990w0M1CrUf6iYPDxQZaDoU7Ysqq4DcYLv2IgkwRsd5j9//PM8+NCW03YNFoMwjEjCLlII1Gl6GKwfK/AvXl9navuD/I8Pf5UjRyZPy89ZdCyJffUV7L707dz/VI1tf7ePqPfKb4BUCt+/O+H88zehHnjE1JBrlVd8HaeLXi/kwIEQ160QBDP0etOce65NrVZhdnae4xRLgLPvnL24vCIBbf/+I9zzzE7OGxxAPc+qBAFFKenONrHaXYqHJ6j4HjpJEJaFtC323PbdF/2e0rZp7z/M1j/7e2zXRfou7xmoGDkhrQmmZtH66AOn6HuIoQE6StFKFc0gREcxE802wcEJntu9/3RfhlccrRU2Ea5jkYSnp2lh44oij97+BW790rfO6h20bVsUHefF/TJdB/cNN3DH4Hu44+NTqGTmFV/f85k6EqOuugC+dz9DRyaxRgZZ3BWdOrTWHDkyy+rVfvbfCqV2c9FF53LvvQ8v8upeWeI4peQoLHlyeqyvJl6RgDY72+S//s+/w/mhlmMwFieOY7Nq1Ri1qvHqqlRKDFTLvOWGK7DufHE1bq9eZflrr8ApF0k6PeQl57Hz4DjjrTaHp2ZJf6jdv7X3EPd9/pu0Wh2SJMlqfvqlVRzOctJU0Wu3seTpm0nqhSm61TmrgxmYum4pCCF5YQqx+OYb2XLR+7nzvx5EneSM2amg20hoj22k6NjE338U95Y3LvaSTikjIxWS5GjX9NTUVq677oZXXUCLopg47GG8LhbvvlP67PFFf8WUQrTmGCPJPv1/e7EuptF6jTH54ofu4vIRDm06h1X1Gu0v3ka6diX/8b99PFcW+SF0ElLyLVq9s0MtezE5blBOU6rLCli2II0X/60dR4qmM0y5WiZ8/Bm8K8+ujsaXolQqsmpVhX37js4dtVoHWLOmjJRyydW5zwammhFBdHZc9zNqsPqHCdMU/0UUD9xamaH3v42P/sWnOXx4glU/cj2WEGf9KeF00JidxbXP6D/zGU/3m/ew7tEv8u5fXYnlLH5VQwhwyx7CtlGzTdpfvG2xl3TKuPbazTjOLtL06MZUqRTIN2SLgZSCVJnGsuN9nAmebX3OWC1HgDu/9zA3vvfHCf7yH+genkBISXn1clb/zLv52Le+x65d+/jvn/giF190LtPTsy96Any1E3Q71MsOe1/Ev+yUcQbd0AtFSok83jszVXQ+fSuXfQD2v/UmvveVafQiblhtR1J1eqh2F7Qm2bVv8RZzCikUPN7//hvYt+/ji72UMwRN2RO88bLBOU/CPrYlWFa1ebFkoBCS2x6d4fDMsR3HK4Y8fur1I0ThiT0LbEtQkCFjxQa/9ebicdOOluPTjo6+d4QQ7GtIPvvdI3P/dt6qEu+8qkq8gGf0cNXma1tOzIn9jA5oTz21gz/5ynf4rV/5Sbb/wf/CKRe54MO/zu/+97/lsceeBowW3Pbtuxd3oWcwjdkm3tjpO6F1Q8XK4Rf3tDqbqFRKlIKQ48apVNH7h1t589tDBv75j/DNz7WIg8WJauW6TWHmAHH3zLeImQ+vfe0VFIvbOXBgqbS4nBxJkvLJv/wrRkeHX/C5EHhocuZFN/FXXnkJl2/4Mb7+0LEBzbUlrZ0/4DOfPNFZXU2vF77sjLHvu8eMZNVqZd7/6//hmK9ZXnd55o7Pc889D/zwy19+FVrTbLZP6GvP6IB22WUXcNGFG9H1KpbnEjZadPYfZt++3GriRGk1W4xsemEzzqmi2U1w3LNfb1MIAS83Q5cq4lu/xrVX7GXgX/wU//h3vRe07gsBG15TZc/WNnF46gOelPDmn12J89iniJdYiv266y7k4MF/esG/CyFYEmmABbBt23Ns2/bcvF7j+y5XXvjWF/1crxecctPU+IfECLrdHnbaxcrSlX3a7c5pN2xd8NbdcWzOPXctpdLp8QgXAn76A7fwG++4hQvWbeDCn/sJLviZ9/BMu0ujcWLHzxyYmWly/iqfevmM3rucVcQPb+HcI9+lMvjCjYLtSj7wb5Zz4y01Bpd7L1lfEBJGVvt4xRN/G9ZGPa7YHBPc+xBYx3md1vhnmai3ZVksW+YThi984BWLw8zMqLwh5ASZmWlSf5HHcl+s4nSjlCKdj2PFKWTBT7mfeM9b+LX3/TMe27Ob3/jtPyE4xQoRWkOqFUmjg/Br3B5GbHlmF09uffaENSNz4Omnd7Duzn/kt97xPv70K0eYacdLelThFUEIJoprac+8sMXfK1rIb36dm3Y9wc0/+QYeiy7gm38/SWv62F1sue7wrl8c4fzOwxyaLfBPDy1n77M91Mvc2usvreDu3k5Q9BGeS3p4EtJjX6QabZaVT89G83RRLPrUapqpqRd2KY+MbObrX19aogenGtu2Wbt2BdffcCXnXbqZ5wKBYwuc5216klRTqQ2e9rVoDY6lj5mf64aKn3rfO7n6hqvRCsYPHeKRh59g796DzM42UadIymhBAW1sbISfe+dbCJ/czyUXrGblylF27tx7ShbURwiBJ22Cww0i3+KrX7uTPXsOntKf8WogimK+8pVvE0YRv37TjejyCrYe0jyys83+yWDRrSHOFKSUWWrrBNAahHzRlOLIag/3wHPQamBdeyU7PjZDbcSlNRMfU7+vj7qsD5+m/f0nqNgWH3rj5TR+7Xru+9oUD982+aLjAZYteM31BdqfupVk70uk3ZV6oRnoGc6aNctxnOYxYggAQlg4ziYeffTvFmllZzYDA1Xe9vY3cuHlVzIjRvj+s12+cmebbniEf3fLCmRzN2m24ZFC8OTDT5z2NSVJQtQY52feeD4lVyNUQsmXpGnI+vMu4FDHI/Uv5JI1N/HPhmHf49/lU5/8PEFw8iNXCwpoSilQGp0orMkur7/xqlMe0ACEFObjVZo/P1VorfnmN+7mW7fdQ70+wMUXn8stV1/O2OvO544dFrc9MrXg7x0litqys8NM8qUYGhrAabROuDm83j1AbWSUmcPPexMKuOT8BHXPNtIjk8j//lFe/7qf4Il6EWkJDu/qEmWNJAe2d/jTQ0PAj4MGdxd45T3H3akKCTe9f4wLew/T3Lr95H7ZMwzbtvjQh36Mw4e/9oLPlcujbN9+6us+S4W33/ImGstv5iO3z9DsHt3wX3t+jc5z9/NnH/34oowzfezPPs7Q0AC9XkC3G6C1ptPp4fse69at4Kd/5Vf4o6+2afUSPnTz63nr22b4wufnYd10HBYU0KanG4w3myyXgmi6xRUXn8/fno45sOzbhVLP228t54UopZmamuHuux/g7rsf4JxzVvGWX/jdk/qerV6K7Z794rhSCvQ80ubO/d/jumtfw7dvk0SBwnEll91Y5cr2N0kPTwAQfu8h6g9v4Y3r1/CWN9/M7PAG9s5U2LVDsffpLpMHAsKuQqWaDsDEC+9xIaA+5nHj+8Z4/fnjtH7rk+YEtoS46qpLOeecJk8//UIbnpGRzXzjG0/kM6bHQWnFeCOi2T2a/nZtwdsu9fjzD3950a5bo9F60V6HTqfL1q07uOPLX+Qd13+Q//vdcVbV4EtP7zglP3dBAS1NU77/xFZ+8prr0XHKI9977LRcOK01dsVn5+z0Cbdt5pw4ExMzrCnO8vM/upxHdnbYfrBDu5eekMyNJWHFkM8tVw3SfPbVV99IDxzm2son2HTdxXSG1zGyqU75iW8Sff32Y75O90LirduJt27HcR02DQ1w0YY16M2r6Fy/jHZxlBkGmGwXmBjXNKfjuUnV6pDDxVcWOG9FE/v7X6X1u99BLbH3gee5fOhDb2DPnk/yYjNVjrOKLVsefOUXdpZw53fu5Vd/+2pGqiNMNCOiWLN80GPvE/dyONtYnYnccccP+J3XXs9/evc5bLnnazz11KnJOiwooGmt+dRn/om3XXs1ji/5p6/deUoW82I4AyUeu+/xfGj6NNBud/iD3/0vbNy4hiuvvox3v+lies4YTx5IeXx3mwOTAVHywoHOyzdUedtlBcLx7dx562d58MHTn5c/3WitEQV/Xq9Rz2xn4JntDAgBAqKXK2xHMemhCdJDE8DD2MCAlNQLPucuG8RetwqxrIy9YhSkRDebhJ9+nGDvQfR8JN3Oogz9j/3Ya6nVdjE+/kKXBikdut3Cq1Jl/0Q5eHCcj/ynP+LqazYzaDvU6lW8KY/P33pmq8dEUcyf/uFHKRZ9pqcbp6zku+AuxyiKiFVKyXEpFLxTs5rnobXmka3bqAyUufe+R0/5988xdDpdHn/8GR5//Bksy2JkpM5FF2/iXVdcxtBrz+VQr8hz4zGp0ji25Kp1FkeeuZ///Ydfn/OtWwrs3LmPbe/6Mc67+VpUpiuaHDiCmjyBIV99EuqtSqE7XZLnuiTPnYTjg20hHAfhubjv/XF2nMi6F5nVq5fzwQ9exo4dH3vRzztOkfHxkCjK9Vlfikajxe3f+t5iL2Pe9HoBvd6pVTAS83kgCSHmvlhKyR/9/q+z+byN/Myv/T8cPnzqfbCEEEgp57p0zga01vPeHz//up5JFAo+q1aNMTxcB8wmY+/egxw8OP6Kr2Uh1xXmd22Hh+vc+NorcCyLKy6/iNffdT+92+9dyI99xSm89y08fen5tIKQbzz0JLfdfu8Jv28W4561bYsPf/gXKZe/zfT0sy/6NfX6BrZtu4K/+IvPnsyPWkwe1lpfOd8XnanPgzOJ492zCz6hKaX4w//3ryiXS6clmIF5gJ5NwWyp0esFryppscnJGb5467cBsC3Ja8/gGsQPk/g+/+UTX2THjhc2VpyJXHPNZtavb/LMM8evnVQqq9i+fen5FOacPk5K5K/V6nDo0Cu/W8/JOd0EUYLI/PnOFs6W9G+5XOSnfuoN7NnzDV4qV+v7Y+zde/iVW1jOWU/uK5KT8yLs3ncQce45i72ME0MIkhXLTrlaz+lASsnP/dw/w7bvp9d7qflHAdSZmFj4jGTOq488oOXkvAjPPLOLfeefg7Xs9EsFnSz26uU85rlndJt2n9e+9nKuv95h//7vv+TX2bZHq+XRanVeoZXlLAXygJaT80OMjY1w7TWbuX98iuof/lvk0MBiL+m42OtW0vyl9/OXn/36y9p8LDYrVizjl37pJnbu/MILJK5+mFJplO3bZ4jjF+pl5uQcj1yCPSfneaxdu4K//pUPUb3rftT9j9O7/3GEZS32sl6I6+BesIF97/1xfuf/fJbnTqbl/xVgYKDCv//372dy8itE0cu7ZdRq67j99t2nf2E5S4r5BrRJ4Oxoo1oc1i72AnJOjmuv3kzl9nvpnYlzPa6Ds3419g1XcGTjWu49PMHf/69PLcoYxXyo1Sr83u/9NJ53J+PjL96i/8O4bpWpqVOvD5uztJlXQNNaj5yuheTkLDZvuOka/tVF5xL+t4/P74W2bSxcTnWXoSWxBgdwNq1DX3Ex42Mj3Dc+xbfvfZin/u9Xzwp90w0b1vAbv/FuLOs7jI+fuERarzfO6OiZX7/MObPIU445OZgh/rdffznWX3yaNGtEsFaOIssldKeLTlJUO2tQSFJ05tLrnLOa7s//BLoXUJqaxT40gdp7kPTIFGq2iU5SdC84sWAnBHJoAOfcdYhLz2Nm9XKeCSMe2r6Hh277Lnv3HjrlygqnC89zeec7b+bd776AAwe+yNTU/BI7Ydhg1aqzpMs054whD2g5OUC9XuOSok+ayV4Jz8X92ffwlV5At9WhVi4yYJu3y2CxgJcFtCnb5o//16dpNFoMDtZYuXKUNeesZu11r2FFtcy1G9YQ/NuPoKZnX3YNolSg/lv/kofrNT76559ix6e/QqfTO2vmy8C05Z9//np+/uffysjITrZt+wvSdP7jBIODF7Jly6lRYM959ZAHtJwcIAxDJm2LtZdsQk3NEP/SB/nY0zv59D9+7QWddpZ11AzUqNmYjr1ms83u3Qfoi2Vde+1lXNnqoJ7v5SUE2Ba8SPeebneZ/v0/4/wPvp13/ugN/M+PH6Td7p6W3/dUY9s2F198Lu97381s3Bixf/+t7Ny5sHK7bReIovU88sjJ+2PlvLqYl5Zjzukh1257eV4JLccNG9bw5puvY8OKZXz9uw/x7Tt+sJAfCRh/tY/+x3/Na/76s6TPa9oovufNpG+6Ae/+x+nd8yA6ikkOT8Dz3SSEwLtmM9tueSP/+g//4rTXyk6FluMv//IHuOWWdezffxfN5r6TOlUOD1/AnXeW+cQnbl3w9zhDyLUcTxPHu2fzgHYGIISYIO8efSnWLrQhKb+2L8uCrm1+XU+I/NqeHo57XfOAlpOTk5OzJMiVQnJycnJylgR5QMvJycnJWRLkAS0nJycnZ0mQB7ScnJycnCVBHtBycnJycpYEeUDLycnJyVkS5AEtJycnJ2dJkAe0nJycnJwlQR7QcnJycnKWBP8/VTrejIik4dgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1,2,0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "列举RGB颜色值和类名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = ['background', 'aeroplane', 'bicycle', 'bird', 'boat',\n",
    "               'bottle', 'bus', 'car', 'cat', 'chair', 'cow',\n",
    "               'diningtable', 'dog', 'horse', 'motorbike', 'person',\n",
    "               'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "查找标签中每个像素的类索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"构建从RGB到VOC类别索引的映射。\"\"\"\n",
    "    colormap2label = torch.zeros(256 ** 3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[\n",
    "            (colormap[0] * 256 + colormap[1]) * 256 + colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"将VOC标签中的RGB值映射到它们的类别索引。\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256\n",
    "           + colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "例如"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "使用图像增广中的随机裁剪，裁剪输入图像和标签的相同区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"随机裁剪特征和标签图像。\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "自定义语义分割数据集类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"一个用于加载VOC数据集的自定义数据集。\"\"\"\n",
    "\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [self.normalize_image(feature)\n",
    "                         for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float())\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [img for img in imgs if (\n",
    "            img.shape[1] >= self.crop_size[0] and\n",
    "            img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(voc_train, batch_size, shuffle=True,\n",
    "                                    drop_last=True,\n",
    "                                    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "整合所有组件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"加载VOC语义分割数据集。\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012', os.path.join(\n",
    "        'VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size,\n",
    "        shuffle=True, drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
 ],
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  "language_info": {
   "name": "python"
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   "scroll": true
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 },
 "nbformat": 4,
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}